#In order to regulate and prevent congestion in AI networks
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Tech Breakdown: What Is a SuperNIC? Get the Inside Scoop!
The most recent development in the rapidly evolving digital realm is generative AI. A relatively new phrase, SuperNIC, is one of the revolutionary inventions that makes it feasible.
Describe a SuperNIC
On order to accelerate hyperscale AI workloads on Ethernet-based clouds, a new family of network accelerators called SuperNIC was created. With remote direct memory access (RDMA) over converged Ethernet (RoCE) technology, it offers extremely rapid network connectivity for GPU-to-GPU communication, with throughputs of up to 400Gb/s.
SuperNICs incorporate the following special qualities:
Ensuring that data packets are received and processed in the same sequence as they were originally delivered through high-speed packet reordering. This keeps the data flow’s sequential integrity intact.
In order to regulate and prevent congestion in AI networks, advanced congestion management uses network-aware algorithms and real-time telemetry data.
In AI cloud data centers, programmable computation on the input/output (I/O) channel facilitates network architecture adaptation and extension.
Low-profile, power-efficient architecture that effectively handles AI workloads under power-constrained budgets.
Optimization for full-stack AI, encompassing system software, communication libraries, application frameworks, networking, computing, and storage.
Recently, NVIDIA revealed the first SuperNIC in the world designed specifically for AI computing, built on the BlueField-3 networking architecture. It is a component of the NVIDIA Spectrum-X platform, which allows for smooth integration with the Ethernet switch system Spectrum-4.
The NVIDIA Spectrum-4 switch system and BlueField-3 SuperNIC work together to provide an accelerated computing fabric that is optimized for AI applications. Spectrum-X outperforms conventional Ethernet settings by continuously delivering high levels of network efficiency.
Yael Shenhav, vice president of DPU and NIC products at NVIDIA, stated, “In a world where AI is driving the next wave of technological innovation, the BlueField-3 SuperNIC is a vital cog in the machinery.” “SuperNICs are essential components for enabling the future of AI computing because they guarantee that your AI workloads are executed with efficiency and speed.”
The Changing Environment of Networking and AI
Large language models and generative AI are causing a seismic change in the area of artificial intelligence. These potent technologies have opened up new avenues and made it possible for computers to perform new functions.
GPU-accelerated computing plays a critical role in the development of AI by processing massive amounts of data, training huge AI models, and enabling real-time inference. While this increased computing capacity has created opportunities, Ethernet cloud networks have also been put to the test.
The internet’s foundational technology, traditional Ethernet, was designed to link loosely connected applications and provide wide compatibility. The complex computational requirements of contemporary AI workloads, which include quickly transferring large amounts of data, closely linked parallel processing, and unusual communication patterns all of which call for optimal network connectivity were not intended for it.
Basic network interface cards (NICs) were created with interoperability, universal data transfer, and general-purpose computing in mind. They were never intended to handle the special difficulties brought on by the high processing demands of AI applications.
The necessary characteristics and capabilities for effective data transmission, low latency, and the predictable performance required for AI activities are absent from standard NICs. In contrast, SuperNICs are designed specifically for contemporary AI workloads.
Benefits of SuperNICs in AI Computing Environments
Data processing units (DPUs) are capable of high throughput, low latency network connectivity, and many other sophisticated characteristics. DPUs have become more and more common in the field of cloud computing since its launch in 2020, mostly because of their ability to separate, speed up, and offload computation from data center hardware.
SuperNICs and DPUs both have many characteristics and functions in common, however SuperNICs are specially designed to speed up networks for artificial intelligence.
The performance of distributed AI training and inference communication flows is highly dependent on the availability of network capacity. Known for their elegant designs, SuperNICs scale better than DPUs and may provide an astounding 400Gb/s of network bandwidth per GPU.
When GPUs and SuperNICs are matched 1:1 in a system, AI workload efficiency may be greatly increased, resulting in higher productivity and better business outcomes.
SuperNICs are only intended to speed up networking for cloud computing with artificial intelligence. As a result, it uses less processing power than a DPU, which needs a lot of processing power to offload programs from a host CPU.
Less power usage results from the decreased computation needs, which is especially important in systems with up to eight SuperNICs.
One of the SuperNIC’s other unique selling points is its specialized AI networking capabilities. It provides optimal congestion control, adaptive routing, and out-of-order packet handling when tightly connected with an AI-optimized NVIDIA Spectrum-4 switch. Ethernet AI cloud settings are accelerated by these cutting-edge technologies.
Transforming cloud computing with AI
The NVIDIA BlueField-3 SuperNIC is essential for AI-ready infrastructure because of its many advantages.
Maximum efficiency for AI workloads: The BlueField-3 SuperNIC is perfect for AI workloads since it was designed specifically for network-intensive, massively parallel computing. It guarantees bottleneck-free, efficient operation of AI activities.
Performance that is consistent and predictable: The BlueField-3 SuperNIC makes sure that each job and tenant in multi-tenant data centers, where many jobs are executed concurrently, is isolated, predictable, and unaffected by other network operations.
Secure multi-tenant cloud infrastructure: Data centers that handle sensitive data place a high premium on security. High security levels are maintained by the BlueField-3 SuperNIC, allowing different tenants to cohabit with separate data and processing.
Broad network infrastructure: The BlueField-3 SuperNIC is very versatile and can be easily adjusted to meet a wide range of different network infrastructure requirements.
Wide compatibility with server manufacturers: The BlueField-3 SuperNIC integrates easily with the majority of enterprise-class servers without using an excessive amount of power in data centers.
#Describe a SuperNIC#On order to accelerate hyperscale AI workloads on Ethernet-based clouds#a new family of network accelerators called SuperNIC was created. With remote direct memory access (RDMA) over converged Ethernet (RoCE) te#it offers extremely rapid network connectivity for GPU-to-GPU communication#with throughputs of up to 400Gb/s.#SuperNICs incorporate the following special qualities:#Ensuring that data packets are received and processed in the same sequence as they were originally delivered through high-speed packet reor#In order to regulate and prevent congestion in AI networks#advanced congestion management uses network-aware algorithms and real-time telemetry data.#In AI cloud data centers#programmable computation on the input/output (I/O) channel facilitates network architecture adaptation and extension.#Low-profile#power-efficient architecture that effectively handles AI workloads under power-constrained budgets.#Optimization for full-stack AI#encompassing system software#communication libraries#application frameworks#networking#computing#and storage.#Recently#NVIDIA revealed the first SuperNIC in the world designed specifically for AI computing#built on the BlueField-3 networking architecture. It is a component of the NVIDIA Spectrum-X platform#which allows for smooth integration with the Ethernet switch system Spectrum-4.#The NVIDIA Spectrum-4 switch system and BlueField-3 SuperNIC work together to provide an accelerated computing fabric that is optimized for#Yael Shenhav#vice president of DPU and NIC products at NVIDIA#stated#“In a world where AI is driving the next wave of technological innovation#the BlueField-3 SuperNIC is a vital cog in the machinery.” “SuperNICs are essential components for enabling the future of AI computing beca
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DIGITAL HEALTH BRIEFING: US telehealth restrictions loosened after Trump request — AI-powered health app raises $47 million — Polar opens API
Welcome to Digital Health Briefing, a new morning email providing the latest news, data, and insight on how digital technology is disrupting the healthcare ecosystem, produced by BI Intelligence.
Sign up and receive Digital Health Briefing free to your inbox.
Have feedback? We'd like to hear from you. Write me at: [email protected] .
TELEHEALTH RESTRICTIONS LOOSENED AFTER TRUMP REQUEST: Restrictions on telehealth services are being loosened after acting Health and Human Services (HHS) Secretary Eric D. Hargan declared the opioid epidemic a public health emergency at the request of US President Donald Trump. HHS stated that it would expand access to telemedicine services on addiction treatment, which includes remote prescribing of medicines commonly used to treat substance abuse or mental health. Telemedicine, a part of telehealth, relates to the use of telecommunications for remote diagnosis and treatment of patients.
The HHS is likely hoping that the expansion of telemedicine access will help address existing limits in health care that are making it more difficult to combat the opioid epidemic. Telemedicine could help overcome these barriers in a number of ways:
Improving access to prevention, treatment, and recovery support services. Telehealth gives patients in rural and remote areas access to treatments and support services that they may otherwise be unable to take advantage of. In some cases, this might include remote prescription fulfillment and diagnoses for addiction.
Strengthening health data collection and sharing. Telehealth simplifies data collection from patients and sharing between facilities and research centers. This data can be used to improve research and treatment. In a 2017 survey of medical professionals, the ability to send clinical documentation via telemedicine technologies was rated as critical or valuable by 80% of respondents, according to REACH Health.
If telemedicine is successful in solving existing shortcomings in the healthcare industry, we could see an acceleration of telemedicine-related regulations. This could help drive adoption of the technology in the US. The US telemedicine market is projected to grow at an annualized rate of 6% over the next three years to reach almost $7 billion in value by 2020, according to Orbis research.
BI Intelligence
Enjoy reading this briefing? Sign up and receive Digital Health Briefing to your inbox.
AI-POWERED HEALTH APP RAISES $47 MILLION IN LATEST FUNDING ROUND: Ada Health, a Berlin-based artificial intelligence (AI) health app, raised 40 million euros ($47 million) in its latest round of funding led by Access Industries. Ada Health is one of the fastest growing medical apps of 2017, TechCrunch reports, and has already been used by more than 1.5 million people since launching in late 2016. The app works by having its AI, called “Ada,” ask a series of personalized questions about the user’s ailments in order to provide the user with a list of possible causes of their symptoms. It then connects the user with real-world doctors. The company plans to use the funding to improve the functionality of its app, onboard new hires, and expand its footprint in the US with a new office. AI-powered health management solutions, such as Ada, will become increasingly popular with consumers as the experience is fine-tuned and awareness of these services grow. The health intelligent virtual assistant market is projected to grow at an annualized rate of 31% between 2017 and 2024 to exceed $1.5 billion in value by the end of the forecast period, according to Global Market Insights.
5G WILL HAVE A SIGNIFICANT IMPACT ON HEALTH CARE INDUSTRY: The rollout of 5G will be a significant driver of growth in the health care sector, enabling more than $1 trillion in sales globally by 2035, according to a Qualcomm report conducted by IHS Markit. The higher speeds of 5G networks — possibly up to 12 times faster than 4G LTE — will be able to support devices that are beyond the capabilities of existing tech, such as remote surgery, high-fidelity virtual reality, and more reliable IoT for use in hospitals. Outside of the monetary impact of 5G, the network standard will also help usher in a new era of “personalized health care,” in which massive volumes of patient data can be used to develop predictive analytics which can then be tailored to an individual patient and their illness.
BI Intelligence
POLAR OPENS PLATFORM TO THIRD-PARTY DEVELOPERS: Sports technology company, Polar Electro, announced that it will open its application programming interface (API) to third-party developers to build apps that use Polar data, according to Wareable. The API gives any user with a Polar Flow account access to training and daily activity data from Polar’s smartwatch and fitness trackers. However, Polar device users need to give permission before their data can be accessed. Health and fitness data is valuable in part because it’s a verifiable measurement of patient/customer behavior. Insurers can use health data to reward customers engaging in good behaviors that maintain a healthy lifestyle. That can save these companies on costs associated with chronic illnesses. More generally, remote monitoring for congestive heart failure patients alone could save up to $10 billion in the US each year for invested healthcare businesses, Deloitte estimates. Insurers are already offering incentives to encourage consumers to provide access to their health and fitness data. US health insurer, Aetna began offering a discount on Apple Watches to its employees in September 2016, for example. Moreover, 63% of insurance companies believe that wearable technologies will be adopted broadly by the insurance industry within the next two years, according to a 2015 Accenture survey. These incentives could be offered in form of discounts for Polar devices as well.
MINTHEALTH ANNOUNCEMENT: Last week, MintHealth announced the launch of a personal health data record that aims to give patients ownership of their health data and oversees permissions to it, according to MobiHealthNews. The platform will use blockchain technology, to provide individuals with a global identifier, which they can use to access their health data in real-time through a mobile or web app. The technology also allows any healthcare provider to access a patient’s data, once the patient has given them permission. MintHealth is aimed at helping solve the issue of interoperability of electronic health records (EHR) between patients, insurers, and medical professionals, which can cause treatment bottlenecks. A survey by eHealth Initiative of provider organizations and health insurance exchange businesses found that 71% of participants said strong interoperability is a key IT requirement for a successful transition to value-based care, while 68% of those surveyed said that current interoperability solutions in the market are not meeting their needs. MintHealth plans to drive usage by selling digital tokens, or “vidaments,” to participating health insurers, which can then be offered to customers for practicing healthy behaviors. Customers can use vidaments to pay for healthcare-related costs such as co-pays, premiums, and pharmacy expenses.
BI Intelligence
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DIGITAL HEALTH BRIEFING: US telehealth restrictions loosened after Trump request — AI-powered health app raises $47 million — Polar opens API
Welcome to Digital Health Briefing, a new morning email providing the latest news, data, and insight on how digital technology is disrupting the healthcare ecosystem, produced by BI Intelligence.
Sign up and receive Digital Health Briefing free to your inbox.
Have feedback? We'd like to hear from you. Write me at: [email protected] .
TELEHEALTH RESTRICTIONS LOOSENED AFTER TRUMP REQUEST: Restrictions on telehealth services are being loosened after acting Health and Human Services (HHS) Secretary Eric D. Hargan declared the opioid epidemic a public health emergency at the request of US President Donald Trump. HHS stated that it would expand access to telemedicine services on addiction treatment, which includes remote prescribing of medicines commonly used to treat substance abuse or mental health. Telemedicine, a part of telehealth, relates to the use of telecommunications for remote diagnosis and treatment of patients.
The HHS is likely hoping that the expansion of telemedicine access will help address existing limits in health care that are making it more difficult to combat the opioid epidemic. Telemedicine could help overcome these barriers in a number of ways:
Improving access to prevention, treatment, and recovery support services. Telehealth gives patients in rural and remote areas access to treatments and support services that they may otherwise be unable to take advantage of. In some cases, this might include remote prescription fulfillment and diagnoses for addiction.
Strengthening health data collection and sharing. Telehealth simplifies data collection from patients and sharing between facilities and research centers. This data can be used to improve research and treatment. In a 2017 survey of medical professionals, the ability to send clinical documentation via telemedicine technologies was rated as critical or valuable by 80% of respondents, according to REACH Health.
If telemedicine is successful in solving existing shortcomings in the healthcare industry, we could see an acceleration of telemedicine-related regulations. This could help drive adoption of the technology in the US. The US telemedicine market is projected to grow at an annualized rate of 6% over the next three years to reach almost $7 billion in value by 2020, according to Orbis research.
Enjoy reading this briefing? Sign up and receive Digital Health Briefing to your inbox.
AI-POWERED HEALTH APP RAISES $47 MILLION IN LATEST FUNDING ROUND: Ada Health, a Berlin-based artificial intelligence (AI) health app, raised 40 million euros ($47 million) in its latest round of funding led by Access Industries. Ada Health is one of the fastest growing medical apps of 2017, TechCrunch reports, and has already been used by more than 1.5 million people since launching in late 2016. The app works by having its AI, called “Ada,” ask a series of personalized questions about the user’s ailments in order to provide the user with a list of possible causes of their symptoms. It then connects the user with real-world doctors. The company plans to use the funding to improve the functionality of its app, onboard new hires, and expand its footprint in the US with a new office. AI-powered health management solutions, such as Ada, will become increasingly popular with consumers as the experience is fine-tuned and awareness of these services grow. The health intelligent virtual assistant market is projected to grow at an annualized rate of 31% between 2017 and 2024 to exceed $1.5 billion in value by the end of the forecast period, according to Global Market Insights.
5G WILL HAVE A SIGNIFICANT IMPACT ON HEALTH CARE INDUSTRY: The rollout of 5G will be a significant driver of growth in the health care sector, enabling more than $1 trillion in sales globally by 2035, according to a Qualcomm report conducted by IHS Markit. The higher speeds of 5G networks — possibly up to 12 times faster than 4G LTE — will be able to support devices that are beyond the capabilities of existing tech, such as remote surgery, high-fidelity virtual reality, and more reliable IoT for use in hospitals. Outside of the monetary impact of 5G, the network standard will also help usher in a new era of “personalized health care,” in which massive volumes of patient data can be used to develop predictive analytics which can then be tailored to an individual patient and their illness.
POLAR OPENS PLATFORM TO THIRD-PARTY DEVELOPERS: Sports technology company, Polar Electro, announced that it will open its application programming interface (API) to third-party developers to build apps that use Polar data, according to Wareable. The API gives any user with a Polar Flow account access to training and daily activity data from Polar’s smartwatch and fitness trackers. However, Polar device users need to give permission before their data can be accessed. Health and fitness data is valuable in part because it’s a verifiable measurement of patient/customer behavior. Insurers can use health data to reward customers engaging in good behaviors that maintain a healthy lifestyle. That can save these companies on costs associated with chronic illnesses. More generally, remote monitoring for congestive heart failure patients alone could save up to $10 billion in the US each year for invested healthcare businesses, Deloitte estimates. Insurers are already offering incentives to encourage consumers to provide access to their health and fitness data. US health insurer, Aetna began offering a discount on Apple Watches to its employees in September 2016, for example. Moreover, 63% of insurance companies believe that wearable technologies will be adopted broadly by the insurance industry within the next two years, according to a 2015 Accenture survey. These incentives could be offered in form of discounts for Polar devices as well.
MINTHEALTH ANNOUNCEMENT: Last week, MintHealth announced the launch of a personal health data record that aims to give patients ownership of their health data and oversees permissions to it, according to MobiHealthNews. The platform will use blockchain technology, to provide individuals with a global identifier, which they can use to access their health data in real-time through a mobile or web app. The technology also allows any healthcare provider to access a patient’s data, once the patient has given them permission. MintHealth is aimed at helping solve the issue of interoperability of electronic health records (EHR) between patients, insurers, and medical professionals, which can cause treatment bottlenecks. A survey by eHealth Initiative of provider organizations and health insurance exchange businesses found that 71% of participants said strong interoperability is a key IT requirement for a successful transition to value-based care, while 68% of those surveyed said that current interoperability solutions in the market are not meeting their needs. MintHealth plans to drive usage by selling digital tokens, or “vidaments,” to participating health insurers, which can then be offered to customers for practicing healthy behaviors. Customers can use vidaments to pay for healthcare-related costs such as co-pays, premiums, and pharmacy expenses.
Join the conversation about this story »
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Tech Breakdown: What Is a SuperNIC? Get the Inside Scoop!
The most recent development in the rapidly evolving digital realm is generative AI. A relatively new phrase, SuperNIC, is one of the revolutionary inventions that makes it feasible.
Describe a SuperNIC
On order to accelerate hyperscale AI workloads on Ethernet-based clouds, a new family of network accelerators called SuperNIC was created. With remote direct memory access (RDMA) over converged Ethernet (RoCE) technology, it offers extremely rapid network connectivity for GPU-to-GPU communication, with throughputs of up to 400Gb/s.
SuperNICs incorporate the following special qualities:
Ensuring that data packets are received and processed in the same sequence as they were originally delivered through high-speed packet reordering. This keeps the data flow’s sequential integrity intact.
In order to regulate and prevent congestion in AI networks, advanced congestion management uses network-aware algorithms and real-time telemetry data.
In AI cloud data centers, programmable computation on the input/output (I/O) channel facilitates network architecture adaptation and extension.
Low-profile, power-efficient architecture that effectively handles AI workloads under power-constrained budgets.
Optimization for full-stack AI, encompassing system software, communication libraries, application frameworks, networking, computing, and storage.
Recently, NVIDIA revealed the first SuperNIC in the world designed specifically for AI computing, built on the BlueField-3 networking architecture. It is a component of the NVIDIA Spectrum-X platform, which allows for smooth integration with the Ethernet switch system Spectrum-4.
The NVIDIA Spectrum-4 switch system and BlueField-3 SuperNIC work together to provide an accelerated computing fabric that is optimized for AI applications. Spectrum-X outperforms conventional Ethernet settings by continuously delivering high levels of network efficiency.
Yael Shenhav, vice president of DPU and NIC products at NVIDIA, stated, “In a world where AI is driving the next wave of technological innovation, the BlueField-3 SuperNIC is a vital cog in the machinery.” “SuperNICs are essential components for enabling the future of AI computing because they guarantee that your AI workloads are executed with efficiency and speed.”
The Changing Environment of Networking and AI
Large language models and generative AI are causing a seismic change in the area of artificial intelligence. These potent technologies have opened up new avenues and made it possible for computers to perform new functions.
GPU-accelerated computing plays a critical role in the development of AI by processing massive amounts of data, training huge AI models, and enabling real-time inference. While this increased computing capacity has created opportunities, Ethernet cloud networks have also been put to the test.
The internet’s foundational technology, traditional Ethernet, was designed to link loosely connected applications and provide wide compatibility. The complex computational requirements of contemporary AI workloads, which include quickly transferring large amounts of data, closely linked parallel processing, and unusual communication patterns all of which call for optimal network connectivity were not intended for it.
Basic network interface cards (NICs) were created with interoperability, universal data transfer, and general-purpose computing in mind. They were never intended to handle the special difficulties brought on by the high processing demands of AI applications.
The necessary characteristics and capabilities for effective data transmission, low latency, and the predictable performance required for AI activities are absent from standard NICs. In contrast, SuperNICs are designed specifically for contemporary AI workloads.
Benefits of SuperNICs in AI Computing Environments
Data processing units (DPUs) are capable of high throughput, low latency network connectivity, and many other sophisticated characteristics. DPUs have become more and more common in the field of cloud computing since its launch in 2020, mostly because of their ability to separate, speed up, and offload computation from data center hardware.
SuperNICs and DPUs both have many characteristics and functions in common, however SuperNICs are specially designed to speed up networks for artificial intelligence.
The performance of distributed AI training and inference communication flows is highly dependent on the availability of network capacity. Known for their elegant designs, SuperNICs scale better than DPUs and may provide an astounding 400Gb/s of network bandwidth per GPU.
When GPUs and SuperNICs are matched 1:1 in a system, AI workload efficiency may be greatly increased, resulting in higher productivity and better business outcomes.
SuperNICs are only intended to speed up networking for cloud computing with artificial intelligence. As a result, it uses less processing power than a DPU, which needs a lot of processing power to offload programs from a host CPU.
Less power usage results from the decreased computation needs, which is especially important in systems with up to eight SuperNICs.
One of the SuperNIC’s other unique selling points is its specialized AI networking capabilities. It provides optimal congestion control, adaptive routing, and out-of-order packet handling when tightly connected with an AI-optimized NVIDIA Spectrum-4 switch. Ethernet AI cloud settings are accelerated by these cutting-edge technologies.
Transforming cloud computing with AI
The NVIDIA BlueField-3 SuperNIC is essential for AI-ready infrastructure because of its many advantages.
Maximum efficiency for AI workloads: The BlueField-3 SuperNIC is perfect for AI workloads since it was designed specifically for network-intensive, massively parallel computing. It guarantees bottleneck-free, efficient operation of AI activities.
Performance that is consistent and predictable: The BlueField-3 SuperNIC makes sure that each job and tenant in multi-tenant data centers, where many jobs are executed concurrently, is isolated, predictable, and unaffected by other network operations.
Secure multi-tenant cloud infrastructure: Data centers that handle sensitive data place a high premium on security. High security levels are maintained by the BlueField-3 SuperNIC, allowing different tenants to cohabit with separate data and processing.
Broad network infrastructure: The BlueField-3 SuperNIC is very versatile and can be easily adjusted to meet a wide range of different network infrastructure requirements.
Wide compatibility with server manufacturers: The BlueField-3 SuperNIC integrates easily with the majority of enterprise-class servers without using an excessive amount of power in data centers.
Read more on Govindhtech.com
#nividia#superNic#spectrum#AIapplications#GPU#NVIDIABlueField3#technews#technology#govindhtech#LLM#generative ai
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