Gordon Bell Special Prize Goes to LLM-Based Covid Variant Prediction

November 17, 2022

For three years running, ACM has awarded not only its long-standing Gordon Bell Prize (read more about this year’s winner here!) but also its Gordon Bell Spec Read more…

Gordon Bell Nominee Used LLMs, HPC, Cerebras CS-2 to Predict Covid Variants

November 17, 2022

Large language models (LLMs) have taken the tech world by storm over the past couple of years, dominating headlines with their ability to generate convincing hu Read more…

Cerebras Builds ‘Exascale’ AI Supercomputer

November 14, 2022

Cerebras is putting down stakes to be a player in the AI cloud computing with a supercomputer called Andromeda, which achieves over an exaflops of "AI performan Read more…

Cerebras Chip Part of Project to Spot Post-exascale Technology

October 19, 2022

Cerebras Systems has secured another U.S. government win for its wafer scale engine chip – which is considered the largest chip in the world. The company's chip technology will be part of a research project sponsored by the National Nuclear Security Administration to find... Read more…

Cerebras Proposes AI Megacluster with Billions of AI Compute Cores

September 14, 2022

Chipmaker Cerebras is patching its chips – already considered the world's largest – to create what could be the largest-ever computing cluster for AI computing. A reasonably sized "wafer-scale cluster," as Cerebras calls it, can network together 16 CS-2s into a cluster to create a computing system with 13.6 million cores for natural... Read more…

Cerebras Systems Thinks Forward on AI Chips as it Claims Performance Win

June 22, 2022

Cerebras Systems makes the largest chip in the world, but is already thinking about its upcoming AI chips as learning models continue to grow at breakneck speed. The company’s latest Wafer Scale Engine chip is indeed the size of a wafer, and is made using TSMC’s 7nm process. The next chip will pack in more cores to handle the fast-growing compute needs of AI, said Andrew Feldman, CEO of Cerebras Systems. Read more…

LRZ Adds Mega AI System as It Stacks up on Future Computing Systems

May 25, 2022

The battle among high-performance computing hubs to stack up on cutting-edge computers for quicker time to science is getting steamy as new chip technologies become mainstream. A European supercomputing hub near Munich, called the Leibniz Supercomputing Centre, is deploying Cerebras Systems' CS-2 AI system as part of an internal initiative called Future Computing to assess alternative computing... Read more…

Argonne Talks AI Accelerators for Covid Research

April 28, 2022

As the pandemic swept across the world, virtually every research supercomputer lit up to support Covid-19 investigations. But even as the world transformed, the Read more…

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Whitepaper

Porting CUDA Applications to Run on AMD GPUs

Giving developers the ability to write code once and use it on different platforms is important. Organizations are increasingly moving to open source and open standard solutions which can aid in code portability. AMD developed a porting solution that allows developers to port proprietary NVIDIA® CUDA® code to run on AMD graphic processing units (GPUs).

This paper describes the AMD ROCm™ open software platform which provides porting tools to convert NVIDIA CUDA code to AMD native open-source Heterogeneous Computing Interface for Portability (HIP) that can run on AMD Instinct™ accelerator hardware. The AMD solution addresses performance and portability needs of artificial intelligence (AI), machine learning (ML) and high performance computing (HPC) for application developers. Using the AMD ROCm platform, developers can port their GPU applications to run on AMD Instinct accelerators with very minimal changes to be able to run their code in both NVIDIA and AMD environments.

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Whitepaper

QCT HPC BeeGFS Storage: A Performance Environment for I/O Intensive Workloads

A workload-driven system capable of running HPC/AI workloads is more important than ever. Organizations face many challenges when building a system capable of running HPC and AI workloads. There are also many complexities in system design and integration. Building a workload driven solution requires expertise and domain knowledge that organizational staff may not possess.

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