August 31, 2023
Supercomputing remains largely an on-premises affair for many reasons that include horsepower, security, and system management. Companies need more time to move Read more…
March 21, 2023
If you are a die-hard Nvidia loyalist, be ready to pay a fortune to use its AI factories in the cloud. Renting the GPU company's DGX Cloud, which is an all-inclusive AI supercomputer in the cloud, starts at $36,999 per instance for a month. The rental includes access to a cloud computer with eight Nvidia H100 or A100 GPUs and 640GB... Read more…
February 21, 2023
In an interesting twist on quantum-inspired work making its way into traditional HPC – and in this case a step further into cloud-based HPC – AWS today intr Read more…
December 7, 2022
Ahead of SC22 in Dallas last month, I met up virtually with Ian Colle, general manager of high performance computing at Amazon Web Services. In this fast-paced Read more…
November 30, 2022
AWS has announced three new Amazon Elastic Compute Cloud (Amazon EC2) instances powered by AWS-designed chips, as well as several new Intel-powered instances � Read more…
November 9, 2022
Nvidia does not have all the internal pieces to build out its massive AI computing empire, so it is enlisting software and hardware partners to scale its so-called AI factories in the cloud. The chip maker's latest partnership is with Rescale, which provides the middleware to orchestrate high-performance computing workloads on public and... Read more…
November 1, 2022
Server hardware has taken a backseat to software-defined virtual machines handling datacenter workloads, but HPE is emphasizing the importance of hardware in these virtual operating models. HPE created waves when it released the next-generation ProLiant Gen11 servers with a flagship server based on Arm CPUs, which sent a strong... Read more…
October 18, 2022
Oracle is bringing Nvidia's AI Enterprise software suite alongside thousands of its latest GPUs to its cloud infrastructure, which could fuel the chipmaker’s Read more…
As Federal agencies navigate an increasingly complex and data-driven world, learning how to get the most out of high-performance computing (HPC), artificial intelligence (AI), and machine learning (ML) technologies is imperative to their mission. These technologies can significantly improve efficiency and effectiveness and drive innovation to serve citizens' needs better. Implementing HPC and AI solutions in government can bring challenges and pain points like fragmented datasets, computational hurdles when training ML models, and ethical implications of AI-driven decision-making. Still, CTG Federal, Dell Technologies, and NVIDIA unite to unlock new possibilities and seamlessly integrate HPC capabilities into existing enterprise architectures. This integration empowers organizations to glean actionable insights, improve decision-making, and gain a competitive edge across various domains, from supply chain optimization to financial modeling and beyond.
Data centers are experiencing increasing power consumption, space constraints and cooling demands due to the unprecedented computing power required by today’s chips and servers. HVAC cooling systems consume approximately 40% of a data center’s electricity. These systems traditionally use air conditioning, air handling and fans to cool the data center facility and IT equipment, ultimately resulting in high energy consumption and high carbon emissions. Data centers are moving to direct liquid cooled (DLC) systems to improve cooling efficiency thus lowering their PUE, operating expenses (OPEX) and carbon footprint.
This paper describes how CoolIT Systems (CoolIT) meets the need for improved energy efficiency in data centers and includes case studies that show how CoolIT’s DLC solutions improve energy efficiency, increase rack density, lower OPEX, and enable sustainability programs. CoolIT is the global market and innovation leader in scalable DLC solutions for the world’s most demanding computing environments. CoolIT’s end-to-end solutions meet the rising demand in cooling and the rising demand for energy efficiency.
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