VHDL Tutorial - Complete Guide to VHDL Process Statement for Beginners [20 mins] [Easy Way]

Welcome to this comprehensive VHDL tutorial where we will dive into the VHDL process statement. In this easy-to-follow guide, we will take you through the syntax and usage of the VHDL process statement, catering especially to beginners. This tutorial will provide you with a thorough understanding of the VHDL process and how it can be effectively implemented in your projects.

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Rectangle Gadgets I've been using for Smash I built myself! Its got pretty controllable gamer RGB <3

I open sourced the code for those interested. All done in VHDL on a cheap $13 FPGA board:

5 Reasons for Using an Open Source Register Automation Tool | Agnisys

Register automation is an integral part of IP and SoC development. Long ago,  design, verification, firmware, and documentation teams preferred doing register management manually or each team wrote their own scripts for limited automation. Later, companies started doing this automation at the organization level. Central scripts were written for register automation for design, verification, firmware, and documentation teams, but still each had their own specifications. This led to many iterations between these teams before different collaterals were all brought in sync. As design complexity grew, maintaining these scripts became difficult, and commercial EDA tools took their place. Simultaneously, many open source tools also cropped up that could be used for register automation. Although commercial tools have their own value proposition, open source tools also have their use cases. The five primary reasons why you might use open source tool are:

1. Cost

Open source EDA tools are typically free to use as there is no license fee, support fee, etc. You can just download, install, and get going. Generally, these tools are ideal for students, academicians, and perhaps small companies or cash-starved start-ups. If the cost to fix a bug in the final product developed using an open source tool is less than the cost of a commercial EDA tool for register automation, then it may be beneficial to opt for it. 

For companies, there are a few more factors that affect the cost indirectly;  experienced CAD engineers are required to integrate the tool in the production environment without any compatibility issues. Also, design and verification teams must be able to quickly ramp up on the tool to be able to churn out fully tested and verified designs faster in order to meet the shrinking market window. Some software engineers may also be needed to fix any issues or tailor the open source tool to meet unique requirements.

Considering all the above factors, if you can ensure that the total cost of ownership of an open source tool remains less, then the open source tool can turn out to be cost-effective for your organization. 

If saving money on a commercial tool is more important than the money spent on finding bugs later in the development flow then you can perhaps go with the open source solutions.

2. Features

More options, more confusion! Fewer options, less confusion! 

Generally, commercial EDA tools offer a comprehensive range of features and functionalities, including a rich set of special registers, a large number of properties for customization, etc. as they are developed and maintained by dedicated teams with extensive resources and customer interactions. 

The open source tools may not support comprehensive features and functionality, but with fewer options you are not spoiled for choice. Assess the specific requirements of your project, including design complexity, input specification format (System RDL/IP-XACT/Excel/Document or a mix of these formats), required output collateral formats (Verilog, VHDL, System Verilog, UVM, HTML, PDF, Markdown, etc.), performance targets, and time-to-market constraints. Determine whether the features and capabilities of the open source tool align with these requirements. 

With limited requirements you can be satisfied with a smaller set of features. For example, you may be using just one input specification format so you may not need a tool that supports a mix of formats. Similarly, you may require only design and verification collaterals, so why should you pay for other collaterals such as firmware, documentation, and custom outputs? Also, you may be working on FPGAs so ASIC related features could be of no use to you. You may be dealing with small and fairly simple designs so you may not require high performance features like clock-domain-crossing (CDC), functional safety, and so on. Working across teams and geography may not be important for you, rendering enterprise level features useless for you. 

If you have simple register maps and don’t have any 3rd party IPs in IP-XACT and other formats, then open source may be enough for you.

3. DIY

Companies can start with the open-source software and set up a team of software engineers to modify the code for specific project requirements, tailoring the tools to fit the company's unique needs. The main challenge here is when updates of an open source software are released. It is usually a thrilling adventure into the unknown. Your engineering team may need to spend hours tinkering with config files and compiling the source to maintain compatibility with your production tool flow. Some previous features may suddenly disappear or be implemented differently as these tools are ever evolving. Merging your custom changes to open source code with new updates often requires  a major and costly effort.

If hours spent tinkering with the output generation is not going to cause delay in the project and the cost of dedicating software engineers in developing, refining and maintaining the open source tool for several years is less than the cost of the commercial tools, then open source might be a possible solution. 

4. Support

Many open-source projects have vibrant communities of users and developers who contribute to ongoing development, provide support, and share knowledge. While open source communities are there to help, you need to navigate through different forums for advice. Extensive documentation requires skills to extract the right information or else you can drown in the sea of available materials.

Support can be a weakness for open source tools. Troubleshooting is a costly affair, and often time consuming as well, delaying your critical project. There are no training programs, although there could be numerous tutorials available to help users learn the nitty gritty of the tools. This kind of community based approach to support can make troubleshooting a tedious task, affecting productivity, and risking your project success.

If time to market is not important for your project, then the absence of quick support may be acceptable.

5. Transparency, Scaling and Certification

With open source software, the code transparency can provide reassurance regarding security and reliability. Transparency may also expose vulnerabilities and critical flaws making these tools susceptible to attacks.

Open source tools also need to scale with your company’s evolving needs to support future innovation and competitiveness. Your company’s growth trajectory is linked to the evolution trajectory of the open source tool, which may be good enough for the short term but not  suitable for long term strategy.

In certain industries, such as aerospace, automotive, and medical devices, regulatory compliance is critical. Companies making products in these domains do not have the luxury of using open source tools as they may not offer features and certifications to ensure compliance with industry standards and regulations.

Open source crowdsource development has its advantages but what happens when multiple users have conflicting requirements? One will always need a person to maintain the branch with their changes.

ISO 26262 certification requires that the tool vendor follows standard development processes to ensure tool quality, predictability, and fault management. If certification is not important or necessary then open source software can be used.

Conclusion

Open source register automation tools have their strengths and weaknesses. There are numerous use cases for these tools especially in academics, prototyping, and non-critical projects/products. However, many other industries and applications have requirements that can only be met with commercial register automation solutions. Open source tools may look cost-effective in the short term but, in the long term, the cost of ownership and the risk to the project outweighs the perceived benefits.

Agilex 5 E-Series with Power-Optimized Edge Performance

Intel Agilex 5 FGPA

Agilex 5 E-Series

Altera’s latest mid-range FPGAs, the Agilex 5 FPGAs E-Series, are now supported by the recently released Quartus Prime Software v24.1, which can be downloaded right now. Intel are happy to announce that it is now simpler than ever and completely free of charge to take use of the unmatched capability of Altera’s Agilex 5 FPGAs E-Series with the introduction of the state-of-the-art Quartus Prime Software from Altera.

Intel Agilex 5

Free Licence: Get rid of obstacles. With the help of Quartus Prime Pro Edition Software v24.1, you may use the newest E-Series devices at no cost, enabling you to innovate beyond limits!

Streamlined Design Flow: Use Quartus Prime Software to see the smooth integration of intellectual property (IP)-Centric design flow. Their easily customizable design samples streamline the process of getting started so you can concentrate on what really matters your innovative ideas.

New Embedded Processing Capabilities: Make use of the Simics simulator-supported dual-core ARM Cortex-A76 and dual-core ARM Cortex-A55 of the Agilex 5 SoC FPGA, the industry’s first asymmetric processing complex. Additionally, Agilex 5 FPGAs may be combined with the feature-rich, performance- and space-optimized Nios V soft-processor for smaller embedded FPGA applications. Additionally, they collaborate with a number of partners who provide a top-notch suite of tools to improve your FPGA and embedded development experience, including Arm, Wind River, Siemens, Ashling, MathWorks, and many more.

Comprehensive Intellectual Property (IP) Portfolio: With their tried-and-true IP portfolio for Agilex 5 FPGAs, many of which are free, you may shorten the time it takes to market. Reduce the amount of circuitry used and make design timing closure easier with hard IP solutions for PCI Express, Ethernet, and memory protocols, which also support LPDDR5. With PCS’s Ethernet 10G MAC, you can guarantee deterministic and synchronised communication, enhanced by Time-Sensitive Networking (TSN) features.

This version includes the Video and Vision Processing (VVP) portfolio IP for Agilex 5 FPGAs, which enables the entire portfolio of video solutions, as well as additional IPs supporting MIPI D-PHY and MIPI CSI-2. Begin developing your Agilex 5 FPGA designs and rely on additional validated advanced features like JESD204C IP, ORAN IP, LDPC IP, CPRI, and eCPRI among others.

Unprecedented Capabilities: Altera FPGAs may be programmed with cutting-edge capabilities like the following using the Quartus Prime Pro Edition Software v24.1.

Agilex 5 datasheet

Dashboard for Quartus Software Exploration (Preproduction)

With distinct instances of Quartus Prime software, numerous projects running concurrently may be easily coordinated and the compilation and timing results can be seen.

Fresh Features for Compilation: Generation flow of precompiled components (PCCs)Utilising the new precompiled component (PCC) generation flow during compilation, shorten the time it takes to compile synthesis.Start the Simulator using the Quartus Prime GUI.Effortlessly start simulations straight from the Quartus Prime GUI by using the handy “Tools ➤ Run Simulation” menu item. Remove the need for extra procedures to streamline your workflow and save time.

Features and Improvements of Synthesis

Use the RTL Linter Tool to convert older RTL files to Verilog/VHDL standards with ease, optimise RAM inference for better speed and resource use, and reduce warnings in error-free RTL modules to increase readability while developing.

Improved Timing Indicator

Gain more flexibility in timing analysis and SDC scripting with new scripting options; guarantee design integrity with sign-off capabilities for particular combinational loops; and learn more about timing characteristics with enhanced Chip Planner visualisation of asynchronous clock domain crossings (CDCs).

Innovations in Advanced Link Analysers

Link Builder: Use the brand-new Link Builder tool to quickly and easily build high-speed serial connections. Streamline the connection creation procedure by automatically generating schematics and importing channels and devices.

High DPI Monitor Assistance: Benefit from improved readability and display quality thanks to GUI scaling for high DPI displays and automated DPI recognition. Enjoy enhanced usability and user experience.

Enhanced Data Viewer: With improvements to the Data Viewer, analyse forward error correction (FEC) code word faults more effectively. Error outcomes may be easily interpreted and analysed for more efficient error correction techniques.

Enhancements to Simulation Time:

Easy-to-use UI for automated import of devices and channels and schematics. Agilex 7 IP offers faster simulation times with the updated Q run and FEC models.

Qualities:

R-Tile: Transaction Layer (TL) multi-channel DMA IP (AXI) up to Gen5 x16 For flexibility in incorporating third-party PCIe Switch IP, use the bypass mode. A new design example for Gen5 x4 endpoint configuration is also provided.

F-Tile: Utilising FastSIM to reduce simulation time in PIPE mode and providing Ubuntu driver support for all sample designs.increased compatibility for up to 64 embedded endpoints.For greater coverage, the Debug Tool Kit (DTK) was added to the switch IP.

Become a Part of the Community: Hua Xue, VP & GM Software Engineering, remarked, “Intel’re excited to offer Quartus Prime Software v24.1, a crucial milestone in FPGA design.”

“Now, engineers everywhere can easily access the unmatched potential of Agilex 5 FPGAs E-Series.” Quartus’s simplified design process and these cutting-edge technologies allow engineers to reach their full potential for innovation. With their state-of-the-art processing capabilities, Agilex 5 devices transform embedded FPGA applications. These are enhanced by Quartus’s vast IP portfolio, which includes a variety of solutions like Ethernet, PCI Express, memory protocols like LPDDR5, support for MIPI D-PHY, CSI-2, and a suite of video solutions, among many other IPs.

The Quartus Exploration Dashboard offers a user-friendly interface and optimization recommendations, which further improve the design exploration process. Intel’re pushing both the simplicity of use and the fast compiler technologies with Quartus v24.1’s open access to E-Series FPGAs and a simplified design pipeline to enable engineers and innovators to unleash their creativity like never before.”

Intel Agilex 5 price

Normally marketed to corporations and incorporated into bigger systems, the Intel Agilex 5 FPGAs do not have a set pricing that is made accessible to the general public. A number of variables affect the pricing, including:

Model specifics: The Agilex 5 family has two distinct series (D and E) with differing logic cell characteristics and capacities. Models with additional features will cost more.

Volume: If you buy in large quantities, you may be able to negotiate a lower price with distributors or directly with Intel.

Distributor: Price structures may vary significantly throughout distributors.

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How Many Programming Languages Are There in Computer Science?

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Programming languages are the backbone of computer science, serving as the essential tools that enable humans to communicate with computers effectively. The landscape of programming languages is vast and diverse, with each language designed to address specific needs and challenges in software development.

Evolution of Programming Languages

The journey of programming languages traces back to the early days of computing, where machine code and assembly languages were predominant. Over time, higher-level languages like Fortran and COBOL emerged, simplifying the programming process and making it accessible to a broader audience.

Categorization of Programming Languages

Programming languages can be broadly categorized into high-level and low-level languages. High-level languages, such as Python and Java, offer abstraction and ease of use, while low-level languages, like Assembly, provide more direct control over hardware. Additionally, scripting languages, like JavaScript, and compiled languages, like C++, each play unique roles in the programming landscape.

Popular Programming Languages

Python, known for its readability and versatility, stands out as a popular language for beginners and experienced developers alike. Java, with its "write once, run anywhere" philosophy, finds applications in various domains. C++, recognized for its efficiency, is commonly used in systems programming.

Specialized and Niche Languages

Beyond the mainstream languages, there exists a plethora of specialized and niche languages tailored for specific purposes. Languages like R for data science, Swift for iOS app development, and VHDL for hardware description highlight the diversity in the programming language ecosystem.

The Role of Programming Languages in Software Development

Choosing the right programming language is crucial in software development. The language used impacts factors such as performance, scalability, and maintenance. The dynamic nature of modern applications often involves using multiple languages within a single project, emphasizing the need for developers to be proficient in various languages.

Challenges and Trends

Despite the abundance of choices, programmers face challenges in selecting the most suitable language for a project. The ever-evolving nature of technology introduces new languages and paradigms, making it essential for developers to stay updated. Current trends include the rise of languages like Rust for system-level programming and Julia for scientific computing.

Learning and Mastering Programming Languages

For beginners, choosing the first programming language can be daunting. It's advisable to start with languages like Python, known for its readability and gentle learning curve. Online resources, coding bootcamps, and community support play crucial roles in the learning process. Mastering a language involves consistent practice, working on real-world projects, and seeking mentorship.

Future of Programming Languages

As technology advances, the programming language landscape continues to evolve. The future may witness the emergence of languages tailored for quantum computing, artificial intelligence, and decentralized applications. Additionally, languages focusing on safety and security, like Rust, might gain prominence.

Conclusion

In the ever-expanding realm of programming languages, understanding their diversity, applications, and trends is essential for both beginners and experienced developers. The right language choice can significantly impact the success of a software project. Embracing continuous learning and adaptability will be key in navigating the dynamic landscape of programming languages.

FAQs

How do I choose the right programming language for my project?

Consider factors like project requirements, scalability, and your familiarity with the language.

Are there any languages specifically designed for beginners?

Yes, languages like Python and Scratch are known for their beginner-friendly syntax.https://internshipgate.com/virtual-internship

What is the significance of low-level languages in modern programming?

Low-level languages provide more direct control over hardware, making them crucial for system-level programming and optimization.

How often do new programming languages emerge?

The frequency of new language introductions varies, but the industry witnesses regular innovations and additions.

Can I become a programmer by learning just one programming language?

While it's possible, diversifying your skill set by learning multiple languages can enhance your versatility and marketability.

Advantages of Pursuing Electronics and Communication Engineering

Best Engineering College in Jaipur Rajasthan has courses in Engineering it is the science, skill, and profession of acquiring and applying scientific, economic, social, and practical knowledge, in origin and also building structures, machines, devices, systems, materials, and processes.

Electronics & Communication Engineering  deals with electronic devices, circuits, communication equipment & receiver), integrated circuits (IC), basic electronica analog digital transmission & reception of data, voice, and, video.

Why Study ECE?

Best paid jobs best payable life and respect in the society

Job satisfaction

Global career – works with different worlds on common fact

Variety of career opportunities

Challenging work

Problems will be open-ended

You find a solution and persuade others that yours is the best one.

Respect

Intellectual Development

Develops your ability to think logically and to solve problems for The benefit of society You can choose projects that benefit society and also Clean the environment carbon-free. Developing prosthetic aids for disabled persons and Finding new sources of energy also Financial security so  You will be well paid and Engineering graduates receive the highest starting salary of any discipline, Prestige, Engineers greatly help and sustain our nation's international competitiveness also maintain our standard of living ensure strong national security and protect public safety.

Professional Environment & Creative Thinking

Engineers need to think creatively is greater than ever before.

Technological And Scientific Discovery

Why do only fa ew elements s behave as semiconductors

 Engineering education can help you understand many things in the world of electronics.

 Different Roles, Different Names

Research and Development (R&D): Engineers whose role is to do research and then plan for new products, materials, processes parts, and processes

Production: Supervise the manufacturing of electrical and electronic components and machines.

Analysis and testing: Analyse and test different types of machines and their parts to ensure that they function flawlessly.

Installation: Install electrical machines, instruments, and parts at the client’s location.

Operation &Maintenance: Primary role is to ensure that machinery is working as per specifications

Skill Set Required For Getting Jobs

Project management skills

High level of technical expertise

Good communication skills

Leadership capability

Strong analytical skills

Problem-solving capabilities

Practical/resourceful

Creativity (invention, innovation, thinking outside box)

Why Focus On Practical Knowledge?

Gap the happen engineering course content and the requirements of the engineering services industry

Various system imparts knowledge of various technical/non-technical areas, but it often falls short of meeting the expectations of the real world.

The gap is a fundamental lacuna in the engineering education framework and This is the only profession.

Fresh graduates ramped up quickly to productivity is a key concern across the industry, and graduates sometimes take six months to a year to become productive.

 What Should You Do?

Pay attention to the basics

Strong foundation in the basics of electronics is a must, and Good knowledge of electronic devices and RF, analog Digital and especially CMOS design also Expertise in VLSI, VHDL, FP and systems, and power transmission verification techniques.

Languages, one must be familiar with HDL (Verilog or VHDL), C and C++, and Other skills - domain knowledge of microprocessors, control systems, embedded systems, and circuit and device testing

Get trained to have an extra edge, also Curriculum may not provide all the learning you need.

Work on a system-level design using off-the-shelf ICs The demand for electronics design engineers to have, the domain also software tools expertise is high.

Actively look out for competitions that organizations/educational institutes conduct Initiatives are excellent opportunities to demonstrate creativity, secure mentoring opportunities from industry experts and pa, and participate in exciting, competitive.

Problem-solving and decision-making, abilities, English Communication skills, and organizational management skills for an all-round perspective.

Exploit Your Internship

Unfortunately, many students treat these courses lightly and My advice would be to take the internship seriously, for the soft skills they impart will be invaluable Keep in mind and Grab every opportunity to chat with everyone from senior members to fresh recruits and You’ll learn a lot about the industry, the job, and their expectations.

Know The Industry Trend

Need to be conversant with global trends and pioneering research worldwide To acquaint himself with the challenges that will face in the future, the engineering student should re-examine.

The electronics industry is very large today and there are multiple sub-disciplines Even some software disciplines require a sound knowledge of electronics along with a strong grip on programming.

Understand Your Aptitude

Companies are looking for people who can fix problems with minimal direction and They don’t want to have to tell people to react when fires are burning.

Conclusion

Top Engineering College in Rajasthan says many opportunities – plan your focused area, Work on both mini and major projects also get a deep insight into the technology, and also Write papers for reviewed journals and conferences. Volunteer speaking on your specialized area, Read, Read and Read and Do not postpone the activity and try to finish on the defined date. Work in the team for the project and share ideas, also Be sincere, hard work, and with a good attitude and Look for clarification if you have doubts, so Get one or two internship projects with the industry.

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PCB Assembly Desktop Factory project. Our team

We have many years of experience in developing electronic devices for various customers. When we complete a non-standard task, we often explore new methods and ways to achieve the required result. By accumulating this knowledge, we create solutions to simplify the design and creation of devices. It's time to share some of our solutions with the community now.

Core team:

• 3 full-time hard/firmware engineers • 15-30 years in product R&D and systems engineering • full range of product development jobs: - highlighting the problem - transforming it into a task - searching for possible solutions based on target parameters - analysis and selection of the best option

‍ Application and system programming:

• core team programming languages: C/C++, ASM • compilers: C /C++ (CLI): GCC, IAR, SDCC, C++ Builder, Avocet C, Hi-Tech C • IDE: SlickEdit, emacs, IAR Embedded Workbench, Multi-Edit, eclipse cdt, STM32CubeIDE, Atmel Start, Atmel Studio, NetBeans IDE, Qt Creator • make, cmake, qmake, cvs, subversion, git, etc • experience/projects: - embedded programming z80, MCS-51, AVR, PIC, ARM (7, 9, Cortex), STM8 - RT-tasks under eCos - eCos modules - in-house RTOS for telecom equipment - special Windows-NT services for own hardware - BDOS/BIOS CP/M for Z80CPU hardware emulator - desktop applications for Windows/Linux ‍

Circuit engineering:

• analog: automation, data acquisition, measurements, sound, etc • digital: from simple logic circuits to FPGA/MCU/PSoC • power electronics: experience in DC/DC up to 600W • experience: PSpice, VHDL, Verilog ‍

Electronic devices R&D:

• PCB/PCBA TH/SMD/multilayer w/auto testing @ production cycle • PCBA (bare and cased) thermal calculations • calculation and design of pulse transformers and inductors • 3D housing design • experience: KiCAD, Altium Designer, FreeCAD, OpenSCAD, Fusion360 projects: - wide spectrum of microcontrollers - telecommunication equipment (about 1M subscribers in service) - time measurement equipment for telecom - hardware emulator with a signature analyzer

FPGA VHDL 7 Segment Multiplexing

Toady we are going to explain how to do time division multiple in VHDL language. This project will display a simple method to do the 7 segment multiplexing in VHDL language for Nexys 3 FPGA development board. To further understand the code you may want to look into our previous FPGA LED blinking example, where we explained how the onboard LED can be accessed in VHDL and Verilog and how we can use…

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VHDL Basics - Language for Hardware Design : Know why you need to learn VHDL?

What is VHDL? VHDL, short for Very High-Speed Integrated Circuit Hardware Description Language, is a powerful and widely used language for designing digital circuits and systems. If you're interested in digital electronics or pursuing a career in hardware design, learning VHDL is essential. Why Learn VHDL? Understanding VHDL gives you the ability to design and simulate complex digital systems, ranging from simple logic gates to advanced processors. VHDL allows you to describe the behavior and structure of these circuits accurately, enabling efficient development and debugging. By learning VHDL, you gain the skills to create efficient and reliable hardware designs. How to Learn VHDL? Learning VHDL doesn't have to be intimidating! In this tutorial video, we will guide you through the basics of VHDL, explaining the syntax, data types, and essential concepts. We'll also provide practical examples and hands-on exercises to reinforce your understanding. Whether you're a beginner or have some experience with digital design, this video will help you grasp VHDL quickly. Join Our VHDL Community Connect with fellow VHDL enthusiasts and learners in our vibrant community. Share ideas, ask questions, and collaborate with others passionate about hardware design. Our community is a supportive and engaging space to expand your knowledge and stay updated with the latest VHDL developments. Subscribe to Learn and Grow Community for Regular updates. Subscribe to our community for more informative videos and guidance. Stay tuned for tutorials, tips, and tricks to enhance your skills. Hit the notification bell to never miss an update.

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Subjects/Courses in Degree Of Information technology (IT) - ACEIT

BTech IT syllabus is a mix of theory and practical knowledge. The BTech IT 1st year syllabus at best engineering colleges in Jaipur covers the primary science, math, and engineering subjects. In the 2nd year syllabus, the B. Tech IT programme touches upon the specialized and elective subjects. Important B. Tech IT subjects include digital electronics, programming language, electronic mathematics, etc. For B. Tech IT jobs, graduates become adept at the latest new technologies, arriving at the most optimal solutions (consuming less time and effort) for any technological problems that might occur, whether small or large.

This course is divided into 4 years, 8 semesters that are 2 semesters each year. The marks of the students are based on their performances, in theory, lab work, and research projects assigned to them.

Apart from the chief course, the students of top engineering colleges Jaipur have to study a parallel course which instills helps them in improving and sharpening their skills. The course may also comprise of lectures, tutorials, training, research projects, and workshops. This helps students to learn more. Moreover, it helps in getting hands-on subjects like Discrete Structures, Web Technologies, Android Applications Development, Artificial Intelligence, Design and Analysis of Algorithm, and many other subjects.

Semester-Wise Syllabus For B.Tech IT

B. Tech IT course syllabus is made up of 8 semesters in 4 years. Students study core subjects in the first year and then move to elective subjects according to their interest in the second year. The course also focuses on practical learning through projects and internships. Semester wise subjects are as follows:

1. First Year Syllabus 

a. Semester Ⅰ – It includes subjects like Applied Mathematics, Environment Studies, Engineering Mathematics, Electrical Science, Applied Physics Lab, Programming in C Lab, Engineering Graphics Lab, Engineering Mechanics Lab, English. 

b. Semester Ⅱ – It includes subjects like Applied Mathematics, Applied Physics - II (Modern Physics), Data Structures using C, Applied Chemistry, Elements of Mechanical Engineering, Data Structures Using C Lab, English, Engineering Mechanics, Engineering Graphics.

2. Second Year Syllabus

a. Semester Ⅲ – It includes subjects like Analog Electronics, Database Management Systems, Operating Systems, Object-Oriented Programming using C++, Applied Mathematics – III, Analog Electronics Lab, UNIX Programming Lab – I.

b. Semester Ⅳ – It include subjects like Discrete Mathematics, Communication Systems, Computer Graphics, Management Information System, Digital Electronics, Digital Electronics Lab, Communication Systems Lab.

3. Third Year Syllabus

a. Semester Ⅴ – It include subjects like Software Engineering, VHDL Programming, Computer Architecture, Data Communication & Computer Networks, Java Programming, VHDL Programming Lab, Software Engineering Lab.

b. Semester Ⅵ – It include subjects like Microprocessor, System Programming, E-Commerce and ERP, Advanced Networking, Advanced Java programming, System Programming Lab, Microprocessor Lab.

4. Fourth Year Syllabus 

a. Semester Ⅶ – It include subjects like Artificial Intelligence, Programming with ASP.Net, Software Project Management, Advance DBMS, Operational Research Lab, Mobile Computing, Information Security, Grid Computing.

b. Semester Ⅷ – It include subjects like Digital Image Processing, Information Storage & Management, Project Submission, Comprehension Viva-voce, Network Operating System, Linux Administration, Software Testing & Quality Assurance, Real-time systems.

Types Of Subjects In B. Tech IT

B. Tech IT at best BTech colleges Jaipur includes two kinds of subjects like core and the elective subjects. Along with this, internship and project submissions are included. In this course, students learn through group discussions and presentations prepared by themselves.

a. Core subjects - Some core subjects involve Engineering Mathematics, Basics of Electronics, Computer Languages, Introduction to Web Technology, Operating Systems, Concepts of Database, Software Project Management, Introduction to Microprocessor, Computer Graphics and Simulation, Data Mining and Data Warehousing. 

b. Lab Subjects – Some lab subjects like VHDL Programming Lab, Programming with ASP.Net, Software Engineering Lab, System Programming Lab, Microprocessor Lab.

c. Elective Subjects – Some elective subjects include Introduction to Linux, Penetration Testing, Information Assurance and Security Management for IT, Network Programming, Network Security and Firewalls, Data and Information Security, Human Security, Malware Analysis, Mobile and Wireless Security.

Course Structure For B. Tech IT

B. Tech IT syllabus at engineering colleges Jaipur focuses on building holistic learning of information technology. In the first year, subjects are similar to aspirant studies in class 12. From the second year, core and elective subjects form the main course of the curriculum. In this way, students can choose the topics which are of interest to them. The course structure is a mix of theoretical knowledge and practical use of this knowledge through projects, research papers, group discussions, and internships. The course structure includes Ⅳ Semesters, Core and Elective Subjects, Research Papers, Surveys, Practical, Thesis Writing, Seminars, Projects, etc.

Teaching Methodology And Techniques

Teaching methodology for the students of BTech IT college Jaipur has a mixture of both theoretical as well as practical knowledge. This teaching methodology helps in building a comprehensive understanding of information technology. Through this methodology, students can understand the world of coding, networking, app development, cybersecurity, etc. Some methodology techniques used by colleges are Discussions, Problem-based Projects, E-learning, Co-curricular Activities, Field Trips, Practical Learnings.

Important Facts For Information Technology

This four-year course at private engineering colleges in Jaipur is divided into 8 semesters. The marks are rewarded according to the number of subjects in each semester.

Subjects related to Data Structures and Algorithms, Operating Systems, Parallel Computing, Artificial Intelligence, Computer Graphics, Soft Computing, Genetic Algorithms, Bioinformatics, Virtual Reality, Cloud Computing, Semantic Web Technologies, Software Architecture, Simulation and Modelling, Advances Database Structures, etc., are part of this course.

These subjects help the students gain an insight into various developments in technology and their applications in computer science engineering. A lot of innovation and self-equipped skills would be essential for the duration of this course. Much research and improvisation are required to keep up with the growing trend of producing unique technologies.

Every student of BTech college must score the minimum score to complete the respective course. Everyone should need to undertake a final year project as well. The type and the duration of the project, along with the respective credit score, are decided by the university/college. 

Besides the respective core subjects, a student is free to take up elective courses as well. It is based on their interest and choices. A student can opt-in for such electives at the beginning of any semester at their own discretion. The choices of such electives may vary based on colleges or universities.

An Introduction to SystemVerilog: Overview and Benefits

Are you looking to get up to speed with the basics of SystemVerilog? This introduction will provide a comprehensive overview of SystemVerilog and all its benefits. SystemVerilog is an incredibly powerful programming language and hardware description language (HDL) used for the verification, design, synthesis, emulation, and prototyping of digital circuits.

The language enables users to efficiently create intricate designs that can be tested quickly and accurately for verification purposes, as well as optimized for cost reduction when transferred into silicon.

Regardless of your previous experience level or coding expertise, this guide provides all the essentials needed to understand why so many people are drawn towards using SystemVerilog in their projects.

What is SystemVerilog?

SystemVerilog is an extension of Verilog, which was developed by Accellera to enhance the design, verification, and synthesis of digital circuits and systems. This language provides object-oriented programming features, constrained random testing, assertions, and coverage analysis. It has become a popular language for both design and verification of digital systems, due to its flexibility and functionality.

Evolution of Verilog to SystemVerilog

Verilog was enhanced to SystemVerilog to address the growing complexity of digital circuits and systems. SystemVerilog added features such as object-oriented programming, constrained random testing, assertions, and coverage analysis to improve design verification, modeling, and synthesis.

Features and capabilities of SystemVerilog

Some of the notable features and capabilities of SystemVerilog include:

Object-oriented programming (OOP) features, such as classes, objects, and inheritance, enable modular and reusable design structures.

Constrained random testing (CRT) allows designers to create random input stimulus while constraining the values to ensure proper functionality and performance.

Assertions and coverage analysis enable designers to check the correctness of their designs and ensure that they meet the desired functional and performance requirements.

Design hierarchy and interface modeling enable designers to organize and manage complex designs with multiple modules and interfaces.

Design reuse and system-on-chip (SoC) design capabilities facilitate the creation of complex designs with pre-designed components and IP blocks.

SystemVerilog also includes features for low-power design, testbench automation, and FPGA synthesis.

Advantages of SystemVerilog

Here are some advantages of SystemVerilog:

SystemVerilog code is more concise and requires fewer lines of code compared to Verilog, which can save time and reduce errors.SystemVerilog includes structures and enumerated types that provide a more scalable and efficient way to design and manage complex digital systems. Interfaces in SystemVerilog provide a higher level of abstraction and enable faster design iterations and easier reuse of IP blocks.SystemVerilog is widely supported in electronic design automation (EDA) tools, including Vivado synthesis, which makes it easy to synthesize and implement designs on FPGAs

SystemVerilog vs. Verilog

Verilog is a Hardware Description Language (HDL) used for modeling and structuring electronic systems, while SystemVerilog combines HDL and Hardware Verification Language (HVL) to facilitate modeling, designing, simulating, testing, and implementing electrical systems.

In Verilog, module-level testing is used for the testbench, while SystemVerilog utilizes class-level test benches for more advanced and efficient testing. While Verilog uses C and Fortran programming languages, SystemVerilog is a programming language that combines Verilog, VHDL, and C++. Verilog supports the datatypes Wire and Reg, whereas SystemVerilog includes enum, union, struct, string, and class datatypes, enabling more versatile modeling and verification capabilities.

In addition to the differences mentioned earlier, Verilog and SystemVerilog also differ in terms of programming paradigms and procedural blocks.

Verilog supports the structured programming paradigm, whereas SystemVerilog supports both structured and object-oriented programming paradigms, enabling more advanced and modular designs.

In Verilog, there is a single always block to implement both combinational and sequential logic. However, SystemVerilog has three procedural blocks, namely always_comb, always_ff, and always_latch, that provide more precise control over logic implementation.

Verilog is based on a hierarchical module design, while SystemVerilog is based on classes that provide more sophisticated design and verification capabilities.

Conclusion

SystemVerilog is an incredibly powerful and efficient tool for those wishing to develop digital designs quickly and reliably. Its encapsulation of VHDL and Verilog properties in one language makes it a necessary addition to any collection of digital design tools.

The interface options, including the command line, graphical user interface, as well as self-verification facilities will empower users with greater flexibility as well as a sound verification process. With such a comprehensive package, it is no surprise that SystemVerilog has become so popular in the design world.

Get ahead of the game with SystemVerilog today – we at Maven Silicon are here to help you along your learning journey! Whether you’re just starting out or already familiar with SystemVerilog, contact us today to get started on our SystemVerilog tutorial.

With us, by your side, you’ll soon be confident enough to tackle more complex projects with ease. Don't wait - take the first step now and explore what SystemVerilog can do for you!

Intel FPGAs speed up databases with oneAPI and SIMD orders

A cutting-edge strategy for improving single-threaded CPU speed is Single Instruction Multiple Data (SIMD).

FPGAs are known for high-performance computing via customizing circuits for algorithms. Their tailored and optimized hardware accelerates difficult computations.

SIMD and FPGAs seem unrelated, yet this blog article will demonstrate their compatibility. By enabling data parallel processing, FPGAs can boost processing performance with SIMD. For many computationally intensive activities, FPGA adaptability and SIMD efficiency are appealing.

High-performance SIMDified programming

SIMD parallel processing applies a single instruction to numerous data objects. Special hardware extensions can execute the same instruction on several data objects simultaneously.

SIMDified processing uses data independence to boost software application performance by rewriting application code to use SIMD instructions extensively.

Key advantages of SIMDified processing include:

Increased performance: SIMDified processing boosts computationally intensive software applications.

Integrability: Intrinsics and dedicated data types make SIMDified processing desirable.

SIMDified processing is available on many current processors, giving it a viable option for computational speed improvement.

Despite its benefits, SIMDified processing is not ideal for many applications. Applications with minimal data parallelism will not benefit from SIMDified processing. It is a convincing method for improving data-intensive software applications.

SIMD Portability Supports Heterogeneity

SIMD registers and instructions make up SIMD instruction sets. SIMD intrinsics in C/C++ are the best low-level programming method for performance.

Low-level programming in heterogeneous settings with different hardware platforms, operating systems, architectures, and technologies is difficult due to hardware capabilities, data parallelism, and naming standards.

Specialized implementations limit portability between platforms, hence SIMD abstraction libraries provide a common SIMD interface and abstract SIMD functions. These libraries use C++ template metaprogramming and function template specializations to translate to SIMD intrinsics and potential compensations for missing functions, which must be implemented.

C/C++ libraries let developers construct SIMD-hardware-oblivious application code and SIMD extension code with minimum overhead. Separating SIMD-hardware-oblivious code with a SIMD abstraction library simplifies both sides.

This method has promoted many SIMD libraries and abstraction layers to solve problems:

Examples of SIMD libraries

Google Highway (open-source)

Xsimd (C++ wrapper for SIMD instances)

Such libraries allow SIMDified code to be designed once and specialized for the target SIMD platform by the SIMD abstraction library. Libraries and varied design environments suit SIMD instructions and abstraction.

Accelerating with FPGAs

FPGAs speed software at low cost and power. Traditional FPGAs required a strong understanding of digital design concepts and specific languages like VHDL or Verilog. FPGA-based solutions are harder to access and more specialized than CPU or GPU-based computing platforms due to programming complexity and code portability. Intel oneAPI changes this.

Intel oneAPI is a software development kit that unifies CPU, GPU, and FPGA programming. It supports C++, Fortran, Python, and Data Parallel C++ (DPC++) for heterogeneous computing to improve performance, productivity, and development time.

Since Intel oneAPI can target FPGAs from SYCL/C++, software developers are increasingly interested in using them for data processing. FPGAs can be used with SIMDified applications by adding them as a backend to the SIMD abstraction library. This allows SIMD applications with FPGAs.

SIMD and FPGAs go together Annotations let the Intel DPC++ compiler synthesis C++ code into circuits and auto-vectorize data-parallel processing. Annotating and implementing code arrays as registers on an FPGA removes data access constraints and allows parallel processing from sink to source. This enables SIMD performance acceleration using FPGAs straightforward and configurable.

SIMD abstraction libraries are a logical choice for FPGA SIMD processing. As noted, the libraries support Intel and ARM SIMD instruction set extensions. TSL abstraction library simplifies FPGA SIMD instruction implementation in the following example. The scalar code specifies loading registers, and the pragma unroll attribute tells the DPC++ Compiler to implement all pathways in parallel in the generic element-wise addition example below.

This simple element-wise example has no dependencies, and comparable implementations will work for SIMD instructions like scatter, gather, and store. Optimization can also accelerate complex instructions.

A horizontal reduction requires a compile-time adder tree of depth ld(N), where N is the number of entries. Unroll pragmas with compile-time constants can implement adder trees in a scalable manner, as shown in the following code example.

Software that calls a library of comparable SIMD components can expedite SIMD instructions on Intel FPGAs by adding the examples above.

Intel FPGA Board Support Package adds system benefits. Intel FPGAs use a BSP to describe hardware interfaces and offer a kernel shell.

The BSP enables SYCL Universal Shared Memory (USM), which frees the CPU from data transfer management by exchanging data directly with the accelerator. FPGAs can be coprocessors.

The pre-compiled BSP generates only kernel logic live, reducing runtime.

Intel FPGAs are ideal for SIMD and streaming applications like current composable databases because to their C++/SYCL compatibility, CPU data transfer offloading, and pre-compiled BSPs.

SIMD/FPGA simplicity At SiMoDSIGMOD 2023 in Seattle, USA, Dirk Habich, Alexander Krause, Johannes Pietrzyk, and Wolfgang Lehner of TU Dresden presented their paper “Simplicity done right for SIMDified query processing on CPU and FPGA” on using FPGAs to accelerate SIMD instructions. The work, supported by Intel’s Christian Färber, illustrates how practical and efficient developing a SIMDified kernel in an FPGA is while achieving top performance.

The paper evaluated FPGA acceleration of SIMD instructions using a dual-socket 3rd-generation Intel Xeon Scalable processor (code-named “Ice Lake”) with 36 cores and a base frequency of 2.2 GHz and a BitWare IA-840f acceleration card with an Intel Agilex 7 AGF027 FPGA and 4x 16 GB DDR4 memories.

First, they gradually increased the SIMD instance register width to see how it affected maximum acceleration bandwidth. The first instance, a simple aggregation, revealed that the FPGA accelerator’s bandwidth improves with data width doubling until the global bandwidth saturates an ideal acceleration case.

The second scenario, a filter-count kernel with a data dependency in the last stage of the adder tree, demonstrated similar behavior but saturates earlier at the PCIe link width. Both scenarios demonstrate the considerable speeding gains of natively parallel instructions on a highly parallel architecture and suggest that wide memory accesses could sustain the benefits.

Final performance comparisons compared the FPGA and CPU. CPU and FPGA received the same multi-threaded AVX512-based filter-count kernel. As expected, per-core CPU bandwidth decreased as thread count and CPU core count grew. FPGA performance was peak across all workloads.

Based on this work, the TU Dresden and Intel team researched how to use TSL to use an FPGA as a bespoke SIMD processor.

Read more on Govidhtech.com

Houston Texas Appliance Parts: How Efinix is Conquering the Hurdle of Hardware Acceleration for Devices at the Edge

Houston Texas Appliance Parts

How Efinix is Conquering the Hurdle of Hardware Acceleration for Devices at the Edge

by Houston Texas Appliance Parts on Tuesday 07 March 2023 08:21 AM UTC-05

In previous articles, we established the many ways FPGAs surpass other AI chipsets for running machine learning algorithms at the edge in terms of reconfigurability, power consumption, size, speed, and cost. Moreover, how the microarchitecture-agnostic RISC-V instruction set architecture (ISA) marries up with the architectural flexibility of the FPGA seamlessly. However, the apparent lack of mid-range, cost-effective FPGAs and their less-than-straightforward design flow are a major bottleneck — the software skills required for the fully custom hardware description language (HDL) implementation are difficult to find and often come with a steep learning curve. 

Efinix fills the gap with FPGAs built on the innovative quantum compute fabric made up of reconfigurable tiles known as exchangeable logic and routing (XLR) cells that function as either logic or routing, rethinking the traditional fixed ratio of logic elements (LEs) and routing resources. This allows for a high-density fabric in a small device package where no part of the FPGA is underutilized. The potential of this platform transcends the typical barriers facing edge-based devices today: power consumption, latency, cost, size, and ease of development. 

Possibly the most striking feature of Efinix FPGAs is the ecosystem and state-of-the-art tool flow surrounding it that lowers development barriers, allowing designers to readily implement AI at the edge using the same silicon — from prototype to production. Efinix has embraced the RISC-V, thereby allowing users to create applications and algorithms in software — capitalizing on the ease of programmability of this ISA without being bound to proprietary IP cores such as ARM. Since this is all done with flexible FPGA fabric, users can massively accelerate in hardware. Efinix offers support for both low level and more complex custom instruction acceleration. Some of these techniques include the TinyML accelerator and predefined hardware accelerator sockets. With approaches such as these, the leaps in acceleration accomplished delivers hardware performance while retaining a software-defined model that can be iterated and refined without the need to learn VHDL. This results in blazing-fast speeds for edge devices, all while consuming low power and functioning within a small footprint. This article discusses precisely how the Efinix platform simplifies the entire design and development cycle, allowing users to take advantage of the flexible FPGA fabric for a scalable embedded processing solution. 

Barriers at the edge — a dam-blocking progress 

From massive wireless sensor networks to streaming a high-resolution 360o immersive AR or VR experience, most of the world's data lies at the edge. Disaggregating the compute burden from the cloud and bringing it closer to the devices opens doors for next-generation, bandwidth-hungry, ultra-low-latency applications in autonomous driving, immersive digital experiences, autonomous industrial facilities, telesurgery, and so on. The use cases are endless once the enormous roadblock of transmitting data to and from the cloud is sidestepped. 

However, the very defining factors of low-latency, power-hungry compute at the edge are the very same factors that pose a significant design challenge for these small but prolific power-limited devices. How then is it possible to design a device capable of processing the power-hungry relevant ML algorithms without having to invest in elaborate technologies? The solution has been to implement any hardware deemed sufficient to run the suitable applications and algorithms (e.g., CPU, GPU, ASIC, FPGA, ASSP) while accelerating the more compute-intensive tasks to balance the compute time (latency) and resources used (power consumed). 

As with any innovation, the landscape of deep learning is continually shifting with updating models and optimization techniques, necessitating the use of more agile hardware platforms that can change almost as rapidly as the programs running on them with little to no risk. The parallel processing and flexibility/reconfigurability of FPGAs seem to line up seamlessly with this need. However, making these devices available for mainstream, high-volume applications requires lowering the design barriers for configuring and accelerating the FPGA fabric — a time-consuming process that normally requires a high degree of expertise. Furthermore, traditional accelerators are typically not granular enough and incorporate large pieces of a model that typically do not scale well. They also generally consume far too much power and are, more often than not, proprietary — causing engineers to relearn how to use the vendor-specific platform. 

The Sapphire RISC-V core 

Creating an application on the RISC-V Core in C/C++ 

Efinix squarely addresses all of these potential obstacles by taking on the challenge of making FPGAs available to the AI/ML community in an intuitive way. The RISC-V Sapphire core is fully user configurable through the Efinity GUI; this way, users do not have to know all the VHDL behind implementing the RISC-V in the FPGA and can exploit the straightforward programmability of common software languages (e.g., C/C++). This allows teams to rapidly generate applications and algorithms in software at speed. All the required peripherals and buses can be specified, configured, and instantiated alongside the Sapphire core to deliver a fully configured SoC (Figure 1). This RISC-V capability includes multi-core (up to four cores) support and Linux capability, delivering a high-performance processor cluster to a designer's FPGA application as well as the ability to run applications directly on the Linux operating system. The next step — hardware acceleration — is greatly simplified with hardware-software partitioning; once a designer has perfected their algorithm in software, they can progressively start to accelerate this within the flexible Efinix FPGA fabric. However, before we move on to the next step of hardware acceleration, it would be important to understand the inherent benefits of the RISC-V architecture and how it can be exploited for use within the FPGA fabric. 

Figure 1: The Efinity GUI enables designers to configure their Sapphire RISC-V core (left) along with all the required peripherals and buses in familiar programming languages for a fully configured SoC. This capability is extended to up to four RISC-V cores.

Custom-instruction-capable RISC-V 

The RISC-V architecture is unique in that it does not have all of its instructions defined; instead, there are a few instructions left open for the designer to define and implement. In other words, a custom arithmetic logic unit (ALU) can be created, and it will perform whatever arbitrary function when called upon by the custom instruction (Figure 2). These custom instructions will have the same architecture as the rest of the instructions (e.g., two registers in, one register out) granting a total of eight bytes of data to work with and four bytes that can be passed back to the RISC-V. 

However, since the ALU is built within the FPGA, it can both access and pull data from the FPGA. This allows users to expand beyond the eight bytes of data and make the ALU arbitrarily complex — giving access to data that was put out on the FPGA previously (e.g., access to data from sensors). The ability to have an arbitrarily complex ALU is a multiplying factor for speed when it comes to hardware acceleration. Efinix has taken this ability of the custom instruction and adapted it for the AI and ML communities with the TinyML platform. 

Figure 2: Custom ALUs can be created with the RISC-V where the standard configuration includes two source registers (rs1 and rs2) that are four bytes wide and one destination register (rd) that is four bytes wide.

 The TinyML platform — a library of custom instructions 

Hardware acceleration with the TinyML platform 

The TinyML platform streamlines the process of hardware acceleration where Efinix has taken the compute primitives used in TensorFlow Lite models and created custom instructions to optimize their execution on accelerators in the FPGA fabric (Figure 3). Through this, the standard software-defined models of TensorFlow are absorbed into the RISC-V complex and are accelerated to run at hardware speed, taking advantage of the rich, open-source TensorFlow Lite community. The entire development flow has been streamlined using the popular Ashling tool flow to make setup, application creation, and debugging a simple and intuitive process.

Figure 3: TensorFlow Lite creates a quantized version of standard TensorFlow models and uses a library of functions to allow these models to run on MCUs at the edge. Efinix TinyML takes these TensorFlow Lite models, and using the custom instruction capabilities of the RISC-V core, accelerates them in the FPGA hardware.

Many of the TinyML platform's libraries of custom instructions are all available to the open-source community on the Efinix GitHub for free access to the Efinix Sapphire core and everything that is needed to design and develop highly accelerated edge AI applications. 

Accelerations strategies: an overview 

The combination of the RISC-V core, the Efinix FPGA fabric, and the rich, open-source TensorFlow community allows for creative acceleration strategies that can be broken down into several steps (Figure 4): 

Step 1: Run the TensorFlow Lite model using the Efinity RISC-V IDE, 

Step 2: Use the TinyML accelerator, 

Step 3: User-defined custom instruction accelerator, 

Step 4: Hardware accelerator templates. 

As stated earlier, "Step 1" is a standard process through the Efinity GUI where users can take the Tensorflow Lite models and run it in software on the RISC-V using the very same, familiar process one would with a standard MCU — without having to worry about VHDL. After Step 1, designers will, more often than not, find that the performance of the algorithm they are running is not optimal and therefore requires acceleration. "Step 2" involves hardware-software partitioning where users can implement the fundamental building blocks inside the TensorFlow Lite models and literally click and drag to instantiate custom instructions and get a massive acceleration on the way the model runs on the Sapphire RISC-V core. 

Figure 4: Efinix acceleration strategies.

User-defined custom instruction accelerator 

"Step 3" leaves it open for designers to create their own custom instructions without leveraging the templates found in the TinyML platform, allowing users to innovate and create acceleration on top of the RISC-V core. 

Hardware accelerator templates 

Finally, after the required fundamental elements are now accelerated on the RISC-V, "Step 4" involves burying them inside the free Efinix SoC framework with "sockets" of acceleration. The quantum accelerator socket allows users to "point at" data, retrieve it, and edit its contents to, say, perform a convolution on bigger blocks of data. 

The Sapphire SoC can be used to perform overall system control and execute algorithms that are inherently sequential or require flexibility. As stated earlier, the hardware-software codesign allows users to choose whether to perform this compute in the RISC-V processor or in hardware. In this acceleration methodology, the pre-defined hardware accelerator socket is connected to a direct memory access (DMA) controller and an SoC slave interface for data transfer and CPU control, which may be used for pre-processing/post-processing before or after the AI inference. The DMA controller facilitates communication between the external memory and other building blocks in the design by (Figure 5): 

Storing frames of data into the external memory, 

Sending and receiving data to/from the hardware acceleration block, 

Sending data to the post-processing engine. 

In an image-signal-processing application, this can look like leaving the RISC-V processor to execute the RGB to grayscale conversion as embedded software, while the hardware accelerator performs Sobel edge detection, binary erosion, and binary dilation in the pipelined, streaming architecture of the FPGA (see "Edge Vision SoC User Guide"). This can be scaled up for multi-camera vision systems, allowing companies to turn their designs into a product and deploy them extremely rapidly. 

Figure 5: Sample edge vision SoC framework block diagram.

MediaPipe Face Mesh use case 

The simplicity of this process might be better highlighted with an example. The MediaPipe Face Mesh ML model estimates hundreds of different three-dimensional facial landmarks in real-time. Efinix took this model and deployed it on the Titanium Ti60 development kit running at 300 MHz. As shown in Figure 6, convolutions on the RISC-V core contributed the most to latency. It is worth noting that the FPGA's resource utilization of close to 60% does not actually reflect the size of the ML model. Instead, this is due to the fact that the entire camera subsystem has been instantiated in the FPGA in order to perform acceleration benchmarking in real-time.  

Figure 6: MediaPipe Face Mesh pre-trained network running on the Ti60 development kit showing both latency and resources used.

Simple custom instructions with the TinyML platform (Step 2) 

Creating and running a simple, custom two registers in, one register out convolution instruction shows a four- to five-fold improvement in latency. This improvement continues as custom instructions used to accelerate the ADD, MAXIMUM, and MUL functions. However, latency improvements hit a plateau since the RISC-V is spending less time doing these operations (Figure 7).  

Figure 7: Obvious latency improvements with simple, custom instructions created for CONV, ADD, MAXIMUM, and MUL functions.

Complex instructions with DMA (Step 4) 

An arbitrarily complex ALU is also generated to replace the original CONV. This changes the slope of the original curve and dramatically improves the latency once more. However, FPGA utilization has also jumped up since the complex instruction has taken more resources inside the FPGA. ​O​nce again, the resource bar standing at nearly 100% is simply due the fact that the FPGA here contains the entire camera subsystem for demonstration purposes, what is important to note is the relative decrease in latency and increase in utilization (Figure 8).  

What's more, switching to a larger FPGA, such as the Ti180, would run all of these complex instructions for massive acceleration without using even 50 percent of the FPGA resources available. These apparent tradeoffs are precisely what allow engineers to readily visualize the balancing act between latency, power consumption, and the cost/size of the FPGA. An edge application that has stringent latency requirements but more lenient power constraints could opt to increasingly accelerate the design for a drastic performance improvement. In power constrained applications, this increase in performance can be traded off by reducing the clock speed for a more moderate improvement in performance at a dramatically lower power. 

Figure 8: A larger custom convolution instruction is employed for much more acceleration; however, resources consumed jumps up. Note, the near full utilization of the FPGA is simply due to the fact that the FPGA contains the entire camera subsystem, this would be dramatically lower if the Ti60 was simply running the ML model

A paradigm shift in AI/ML development 

In a nutshell, Efinix has combined the familiar development environment of the RISC-V ISA and exploited its custom instruction capability to function within the architecturally flexible FPGA fabric. Unlike many hardware accelerators, this approach does not require any third-party tools or compilers. The acceleration is also fine grain with the acceleration of machine instructions — a level of granularity that only makes sense with an FPGA. 

The fact that edge devices can be prototyped and deployed on the innovative design architecture of the Efinix FPGA means the solution is future-proofed. New models and updated network architectures can be expressed in familiar software environments and accelerated at the custom instruction level with only a small amount of VHDL (with libraries of available templates to use for guidance). This degree of hardware-software partitioning where 90 percent of the model remains in software running on the RISC-V allows for an extremely fast time to market. The combination of all of these approaches yields an elegant solution that truly lowers the barriers to entry for implementing an edge device. Designers now have access to a world-class embedded processing capability that can be accessed with a state-of-the-art tool flow and instantiated on the revolutionary Efinix Quantum fabric. 

 The post How Efinix is Conquering the Hurdle of Hardware Acceleration for Devices at the Edge   appeared first on EE Times.

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Price: [price_with_discount] (as of [price_update_date] - Details) [ad_1] What’s New in the Third Edition, Revised Printing The same great book gets better! This revised printing features all of the original content along with these additional features: • Appendix A (Assemblers, Linkers, and the SPIM Simulator) has been moved from the CD-ROM into the printed book • Corrections and bug fixes Third Edition features New pedagogical features • Understanding Program Performance - Analyzes key performance issues from the programmer’s perspective • Check Yourself Questions - Helps students assess their understanding of key points of a section • Computers In the Real World - Illustrates the diversity of applications of computing technology beyond traditional desktop and servers • For More Practice - Provides students with additional problems they can tackle • In More Depth - Presents new information and challenging exercises for the advanced student New reference features • Highlighted glossary terms and definitions appear on the book page, as bold-faced entries in the index, and as a separate and searchable reference on the CD. • A complete index of the material in the book and on the CD appears in the printed index and the CD includes a fully searchable version of the same index. • Historical Perspectives and Further Readings have been updated and expanded to include the history of software R&D. • CD-Library provides materials collected from the web which directly support the text. In addition to thoroughly updating every aspect of the text to reflect the most current computing technology, the third edition • Uses standard 32-bit MIPS 32 as the primary teaching ISA. • Presents the assembler-to-HLL translations in both C and Java. • Highlights the latest developments in architecture in Real Stuff sections: - Intel IA-32 - Power PC 604 - Google’s PC cluster - Pentium P4 - SPEC CPU2000 benchmark suite for processors - SPEC Web99 benchmark for web servers - EEMBC benchmark for embedded systems - AMD Opteron memory hierarchy - AMD vs. 1A-64 New support for distinct course goals Many of the adopters who have used our book throughout its two editions are refining their courses with a greater hardware or software focus. We have provided new material to support these course goals: New material to support a Hardware Focus • Using logic design conventions • Designing with hardware description languages • Advanced pipelining • Designing with FPGAs • HDL simulators and tutorials • Xilinx CAD tools New material to support a Software Focus • How compilers work • How to optimize compilers • How to implement object oriented languages • MIPS simulator and tutorial • History sections on programming languages, compilers, operating systems and databases On the CD • NEW: Search function to search for content on both the CD-ROM and the printed text • CD-Bars: Full length sections that are introduced in the book and presented on the CD • CD-Appendixes: Appendices B-D • CD-Library: Materials collected from the web which directly support the text • CD-Exercises: For More Practice provides exercises and solutions for self-study • In More Depth presents new information and challenging exercises for the advanced or curious student • Glossary: Terms that are defined in the text are collected in this searchable reference • Further Reading: References are organized by the chapter they support • Software: HDL simulators, MIPS simulators, and FPGA design tools • Tutorials: SPIM, Verilog, and VHDL • Additional Support: Processor Models, Labs, Homeworks, Index covering the book and CD contents Instructor Support Instructor support provided on textbooks.elsevier.com: • Solutions to all the exercises • Figures from the book in a number of formats • Lecture slides prepared by the authors and other instructors • Lecture notes *For the Revised Printing, Appendix A appears in the printed book rather than on the CD. This is the only change.

*Explains the latest benchmarking software including SPEC CPU2000 suite for processors, SPEC Web99 for web servers, and EEMBC for embedded systems *Features the latest developments of the Intel IA-32 architecture as well as the Power PC 604, the AMD Opteron Memory, and the Intrinsity FastMATH processor. *Compares MIPs assembler code to both C and Java ASIN ‏ : ‎ 0123706068 Publisher ‏ : ‎ Morgan Kaufmann; 3rd edition (27 July 2007); CBS PUBLISHERS & DISTRIBUTORS PVT. LTD 01149349337 Language ‏ : ‎ English Paperback ‏ : ‎ 741 pages ISBN-10 ‏ : ‎ 9780123706065 ISBN-13 ‏ : ‎ 978-0123706065 Item Weight ‏ : ‎ 1 kg 340 g Dimensions ‏ : ‎ 19.69 x 3.18 x 22.86 cm Country of Origin ‏ : ‎ India Net Quantity ‏ : ‎ 1 Count Importer ‏ : ‎ CBS PUBLISHERS AND DSITRIBUTORS PVT LTD PHONE-01149344934 Packer ‏ : ‎ CBS PUBLISHERS AND DISTRIBUTORS PVT LTD PH: 011-49344934 Generic Name ‏ : ‎ Textbook [ad_2]

YoungMinds - VLSI System Design and It’s Importance

Full-form of VLSI is Very Large-Scale Integration, is the process of creating an integrated circuits (IC’s) by combining millions or billions of MOS transistors onto a single chip.

VLSI began in the 1970s when MOS integrated circuit (Metal Oxide Semiconductor) chips were developed and then widely adopted, enabling complex semiconductor and telecommunication technologies. The microprocessor and memory chips are VLSI devices.

VLSI is one of the most widely used technologies for microchip processors, integrated circuits (IC) and component designing. It was initially designed to support hundreds of thousands of transistor gates on a microchip which, as of 2012, exceeded several billion.

In VLSI, the programming languages for IC design are called hardware description languages (HDLs). These include VHDL, Verilog, System Verilog, C, and scripting languages like Perl and TCL. In VLSI, the development methodology a team follows is as important as the HDL used to build a new product.

Few Important Points of VLSI System Design: -

VLSI is a measure of the complexity of an integrated circuit

It deals with the Software

It deals with reading and converting signals from digital to analog and vice versa for a task

Need knowledge of computer programming languages like C, C++

Deals with Internet of things Machine Learning, UI design, Networking

Moreover, as the new-age technologies like machine learning, artificial intelligence, edge computing, cloud, etc. becomes mainstream, it needs to be backed up with highly efficient and specialized chip design. Typically, electronic circuits incorporate a CPU, RAM, ROM, and other peripherals on a single PCBA.

If anyone searching VLSI System Design Services to make your ideas into reality – my best suggestion is “Youngminds” - Realizing product and software development for a wide range of application areas on cutting-edge technologies like electronic chip design flow from specification to GDSII on latest node technologies, with special focus on RTL/FPGA Design, design verification and FPGA emulation.

“Young Minds” VLSI System Design Services: -

Micro-Architecture development for given specifications

SoC Design / ARM-based SoC architecture designs

RTL Integration & IP subsystem development

Full-Chip / SoC Level Design with Verilog, VHDL, System Verilog

Migration from FPGA to ASIC

Lint, CDC Checks and writing waivers

Integration of digital and analog blocks (Like SERDES PMA + PCS or DDR + Phy etc.,)

Synthesis, STA Constraints for both ASIC and FPGA

Logic equivalency and formality checks

Hands-on experience on Various Industrial EDA tools

Optimization of Power, Area and timing tradeoff

FPGA Prototyping on Xilinx / Altera FPGA Boards

High-Speed protocol Interfaces: -

PCIe Gen1,2,3,4,5 With PIPE / SERDES

Ethernet 100G, 40G, 10G, 1G

USB 3.0, USB 2.0 host and device controllers

AXI, AHB

Other Interfaces like APB / SPI / UART / I2C

Not only VLSI System Design and Development Services, the best thing is “Youngminds” is also provides Training Programs to help students / Engineers and customers get to productivity faster.

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