Graphics processing unit

Avgidea Released Greenative, a tool for building and operating LLMs

Retrieved on: 
Friday, January 19, 2024

Avgidea , a developer and consultant for optimized cloud-native services, releases a new tool Greenative (PAT.P in Japan) for building and operating LLMs in your own infrastructure environment and providing interactive chat services to users.

Key Points: 
  • Avgidea , a developer and consultant for optimized cloud-native services, releases a new tool Greenative (PAT.P in Japan) for building and operating LLMs in your own infrastructure environment and providing interactive chat services to users.
  • After installing a base LLM such as Llama 2 from the console, you can build your own LLMs by importing and fine-tuning arbitrary data.
  • The user can then associate the model with a chat thread and start using it immediately.
  • Infrastructure environment: Greenative can utilize various infrastructure environments such as on-premise, virtual environment, and public cloud.

DigitalOcean Announces Availability of NVIDIA H100 GPUs on Paperspace Platform, Expanding Access to AI Compute for Startups and Growing Digital Businesses

Retrieved on: 
Thursday, January 18, 2024

DigitalOcean Holdings, Inc. (NYSE: DOCN), the developer cloud optimized for startups and growing digital businesses, today announced virtualized availability of NVIDIA H100 Tensor Core GPUs on its Paperspace platform .

Key Points: 
  • DigitalOcean Holdings, Inc. (NYSE: DOCN), the developer cloud optimized for startups and growing digital businesses, today announced virtualized availability of NVIDIA H100 Tensor Core GPUs on its Paperspace platform .
  • This provides startups and growing digital businesses with state-of-the-art infrastructure crucial for developing the next generation of artificial intelligence/machine learning (AI/ML) applications.
  • The surge in interest for accelerated AI computing from businesses looking to elevate their capabilities in AI/ML has fueled the demand for NVIDIA H100 GPUs.
  • “While many vendors are optimizing their offerings to serve large enterprises, DigitalOcean is proud to offer startups and growing digital businesses with reliable and flexible access to NVIDIA H100 GPUs,” said Kanishka Roychoudhury, GM of AI/ML at DigitalOcean.

Cadence Unveils New Palladium Z2 Apps with Industry’s First 4-State Emulation and Mixed-Signal Modeling to Accelerate SoC Verification

Retrieved on: 
Thursday, January 18, 2024

The new Cadence® apps and updates individually offer industry-leading performance and features to address these growing challenges.

Key Points: 
  • The new Cadence® apps and updates individually offer industry-leading performance and features to address these growing challenges.
  • “NVIDIA has utilized Cadence Palladium Emulation for many years for our early software development, hardware-software verification and debug tasks.
  • We have worked closely with Cadence to provide input on the new Palladium apps, including the industry’s first Real Number Modeling and 4-State Emulation apps.
  • With the new 4-State Emulation App, we can accelerate the low-power verification of our complex SoC designs, improving our verification accuracy and low-power coverage while improving overall verification throughput.”​

Supermicro Introduces a Rack Scale Total Solution for AI Storage to Accelerate Data Pipelines for High-Performance AI Training and Inference

Retrieved on: 
Thursday, January 25, 2024

SAN JOSE, Calif., Jan. 25, 2024 /PRNewswire/ -- Supermicro, Inc. (NASDAQ: SMCI), a Total IT Solution Manufacturer for AI, Cloud, Storage, and 5G/Edge, is launching full stack optimized storage solution for AI and ML data pipelines from data collection to high performance data delivery. This new solution maximizes AI time-to-value by keeping GPU data pipelines fully saturated. For AI training, massive amounts of raw data at petascale capacities can be collected, transformed, and loaded into an organization's AI workflow pipeline. This multi-tiered Supermicro solution has been proven to deliver multi-petabyte data for AIOps and MLOps in production environments. The entire multi-rack scale solution from Supermicro is designed to reduce implementation risks, enable organizations to train models faster, and quickly use the resulting data for AI inference.

Key Points: 
  • SAN JOSE, Calif., Jan. 25, 2024 /PRNewswire/ -- Supermicro, Inc. (NASDAQ: SMCI), a Total IT Solution Manufacturer for AI, Cloud, Storage, and 5G/Edge, is launching full stack optimized storage solution for AI and ML data pipelines from data collection to high performance data delivery.
  • For AI training, massive amounts of raw data at petascale capacities can be collected, transformed, and loaded into an organization's AI workflow pipeline.
  • The entire multi-rack scale solution from Supermicro is designed to reduce implementation risks, enable organizations to train models faster, and quickly use the resulting data for AI inference.
  • Our new storage solution for AI training enables customers to maximize the usage of our most advanced rack scale solutions of GPU servers, reducing their TCO and increasing AI performance."

Supermicro Introduces a Rack Scale Total Solution for AI Storage to Accelerate Data Pipelines for High-Performance AI Training and Inference

Retrieved on: 
Thursday, January 25, 2024

SAN JOSE, Calif., Jan. 25, 2024 /PRNewswire/ -- Supermicro, Inc. (NASDAQ: SMCI), a Total IT Solution Manufacturer for AI, Cloud, Storage, and 5G/Edge, is launching full stack optimized storage solution for AI and ML data pipelines from data collection to high performance data delivery. This new solution maximizes AI time-to-value by keeping GPU data pipelines fully saturated. For AI training, massive amounts of raw data at petascale capacities can be collected, transformed, and loaded into an organization's AI workflow pipeline. This multi-tiered Supermicro solution has been proven to deliver multi-petabyte data for AIOps and MLOps in production environments. The entire multi-rack scale solution from Supermicro is designed to reduce implementation risks, enable organizations to train models faster, and quickly use the resulting data for AI inference.

Key Points: 
  • SAN JOSE, Calif., Jan. 25, 2024 /PRNewswire/ -- Supermicro, Inc. (NASDAQ: SMCI), a Total IT Solution Manufacturer for AI, Cloud, Storage, and 5G/Edge, is launching full stack optimized storage solution for AI and ML data pipelines from data collection to high performance data delivery.
  • For AI training, massive amounts of raw data at petascale capacities can be collected, transformed, and loaded into an organization's AI workflow pipeline.
  • The entire multi-rack scale solution from Supermicro is designed to reduce implementation risks, enable organizations to train models faster, and quickly use the resulting data for AI inference.
  • Our new storage solution for AI training enables customers to maximize the usage of our most advanced rack scale solutions of GPU servers, reducing their TCO and increasing AI performance."

Google Cloud and Hugging Face Announce Strategic Partnership to Accelerate Generative AI and ML Development

Retrieved on: 
Thursday, January 25, 2024

SUNNYVALE, Calif., Jan. 25, 2024 /PRNewswire/ -- Google Cloud and Hugging Face today announced a new strategic partnership that will allow developers to utilize Google Cloud's infrastructure for all Hugging Face services, and will enable training and serving of Hugging Face models on Google Cloud.

Key Points: 
  • Developers will be able to train, tune, and serve open models quickly and cost-effectively on Google Cloud
    SUNNYVALE, Calif., Jan. 25, 2024 /PRNewswire/ -- Google Cloud and Hugging Face today announced a new strategic partnership that will allow developers to utilize Google Cloud's infrastructure for all Hugging Face services, and will enable training and serving of Hugging Face models on Google Cloud.
  • The partnership advances Hugging Face's mission to democratize AI and furthers Google Cloud's support for open source AI ecosystem development.
  • With this partnership, Google Cloud becomes a strategic cloud partner for Hugging Face, and a preferred destination for Hugging Face training and inference workloads.
  • "Google Cloud and Hugging Face share a vision for making generative AI more accessible and impactful for developers," said Thomas Kurian, CEO at Google Cloud.

Data Center Solutions Market worth $591.7 billion by 2028 - Exclusive Report by MarketsandMarkets™

Retrieved on: 
Wednesday, January 24, 2024

By data center size, the mid-sized data center segment holds the second-largest market share during the forecast period.

Key Points: 
  • By data center size, the mid-sized data center segment holds the second-largest market share during the forecast period.
  • To optimize the use of servers, mid-sized data centers have a high use of virtualized environments, and efficient allocation of data center resources is required.
  • To facilitate high performance, efficient design, and easy deployment, these data centers are increasingly adopting data center transformation services.
  • Data Center Solutions Market Advantages:
    Organisations may effectively increase or contract their computer capabilities in response to demand thanks to the scalable architecture that data centre solutions offer.

Data Center Solutions Market worth $591.7 billion by 2028 - Exclusive Report by MarketsandMarkets™

Retrieved on: 
Wednesday, January 24, 2024

By data center size, the mid-sized data center segment holds the second-largest market share during the forecast period.

Key Points: 
  • By data center size, the mid-sized data center segment holds the second-largest market share during the forecast period.
  • To optimize the use of servers, mid-sized data centers have a high use of virtualized environments, and efficient allocation of data center resources is required.
  • To facilitate high performance, efficient design, and easy deployment, these data centers are increasingly adopting data center transformation services.
  • Data Center Solutions Market Advantages:
    Organisations may effectively increase or contract their computer capabilities in response to demand thanks to the scalable architecture that data centre solutions offer.

Data Center IT Semiconductor Market to Grow to $286 Billion by 2028, According to Dell'Oro Group

Retrieved on: 
Wednesday, January 24, 2024

REDWOOD CITY, Calif., Jan. 24, 2024 /PRNewswire/ -- According to a newly published forecast report by Dell'Oro Group, the trusted source for market information about the telecommunications, security, networks, and data center industries, the worldwide data center IT semiconductors market, which includes the major components for servers and storage systems, is set to achieve a five-year compound annual growth (CAGR) rate of 25 percent, reaching $286 billion by 2028. We project accelerators, consisting mostly of GPUs, to account for nearly half of the total market.

Key Points: 
  • We project accelerators, consisting mostly of GPUs, to account for nearly half of the total market.
  • "In a notable turn of events in 2023, revenues for accelerators surpassed those of CPUs.
  • The server CPU landscape is diversifying, with compelling choices for the x86 and ARM architectures.
  • The diversity is resulting in innovations, with future generations of CPUs set to increase significantly in core count and will be embedded with accelerators.

AI and Semiconductors Spearhead Surge in Server GPU Market with Estimated Growth to $61.7 Billion by 2028

Retrieved on: 
Wednesday, January 24, 2024

The global AI and semiconductor - a server GPU market accounted for $15.4 billion in 2023 and is expected to grow at a CAGR of 31.99% and reach $61.7 billion by 2028.

Key Points: 
  • The global AI and semiconductor - a server GPU market accounted for $15.4 billion in 2023 and is expected to grow at a CAGR of 31.99% and reach $61.7 billion by 2028.
  • A key element of AI and ML is the training of sophisticated neural networks, which is accelerated in large part by GPU servers.
  • The end-use application segment is a part of the application segment for the worldwide AI and semiconductor - server GPU market.
  • GPU servers can transfer certain computations from conventional CPUs to GPU servers, which improves overall performance and reduces energy consumption.