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The New MLPerf Storage Benchmark Runs Without ML Accelerators
MLCommons is known for its independent Machine Learning (ML) benchmarks. These benchmarks have focused on mathematical ML operations and accelerators (e.g., Nvidia GPUs). Recently, MLCommons intr …
DataPelago Unveils Universal Engine to Unite Big Data, Advanced Analytics, HPC, and AI Workloads
DataPelago this week emerged from stealth with a new virtualization layer that it says will allow users to move AI, data analytics, and ETL workloads to whatever physical processor they want, wit …
IBM Quantum Summit Evolves into Developer Conference
October 2, 2024
Instead of its usual quantum summit this year, IBM will hold its first IBM Quantum Developer Conference which the company is calling, “an exclusive, first-of- Read more…
Stayin’ Alive: Intel’s Falcon Shores GPU Will Survive Restructuring
October 2, 2024
Intel's upcoming Falcon Shores GPU will survive the brutal cost-cutting measures as part of its "next phase of transformation." An Intel spokeswoman confirmed t Read more…
A Q&A with Quantum Systems Accelerator Director Bert de Jong
September 30, 2024
Quantum technologies may still be in development, but these systems are evolving rapidly and existing prototypes are already making a big impact on science and Read more…
How GenAI Will Impact Jobs In the Real World
September 30, 2024
There’s been a lot of fear, uncertainty, and doubt (FUD) about the potential for generative AI to take people’s jobs. The capability of large language model Read more…
Intel Customizing Granite Rapids Server Chips for Nvidia GPUs
September 25, 2024
Intel is now customizing its latest Xeon 6 server chips for use with Nvidia's GPUs that dominate the AI landscape. The chipmaker's new Xeon 6 chips, also called Read more…
Granite Rapids HPC Benchmarks: I’m Thinking Intel Is Back (Updated)
September 25, 2024
Waiting is the hardest part. In the fall of 2023, HPCwire wrote about the new diverging Xeon processor strategy from Intel. Instead of a on-size-fits all approa Read more…
Datacenter Appetite: Nuclear is on the Menu
September 24, 2024
Hyperscalers have recently made big moves to secure enough power for their data centers. While renewable sources are preferable, there is not enough capacity to Read more…
Google’s DataGemma Tackles AI Hallucination
September 18, 2024
The rapid evolution of large language models (LLMs) has fueled significant advancement in AI, enabling these systems to analyze text, generate summaries, sugges Read more…
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From Hallucination to Reality
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.
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Whitepaper
Why IT Must Have an Influential Role in Strategic Decisions About Sustainability
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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