Tesla Bulks Up Its GPU-Powered AI Super – Is Dojo Next?

August 16, 2022

Tesla has revealed that its biggest in-house AI supercomputer – which we wrote about last year – now has a total of 7,360 A100 GPUs, a nearly 28 percent uplift from its previous total of 5,760 GPUs. That’s enough GPU oomph for a top seven spot on the Top500, although the tech company best known for its electric vehicles has not publicly benchmarked the system. If it had, it would... 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…

Microsoft’s ‘Singularity’ to Enable Global Accelerator Network for AI Training

February 24, 2022

In science fiction and future studies, the word “singularity” is invoked in reference to a rapidly snowballing artificial intelligence that, repeatedly iterating on itself, eclipses all human knowledge and ability. It is this word that Microsoft—perhaps ambitiously—has invoked for its new AI project, a “globally distributed scheduling service for highly efficient and reliable execution of deep learning training and inference workloads.” Read more…

Cerebras CS-2 Aids in Fight Against SARS-CoV-2

December 21, 2021

Decoding the replication mechanisms of the SARS-CoV-2 virus has been a key research quest as the COVID-19 pandemic continues. For the scientific computin Read more…

Nvidia Dominates Latest MLPerf Results but Competitors Start Speaking Up

December 1, 2021

MLCommons today released its fifth round of MLPerf training benchmark results with Nvidia GPUs again dominating. That said, a few other AI accelerator companies Read more…

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MosaicML, Led by Naveen Rao, Comes Out of Stealth Aiming to Ease Model Training

October 15, 2021

With more and more enterprises turning to AI for a myriad of tasks, companies quickly find out that training AI models is expensive, difficult and time-consuming. Finding a new approach to deal with those cascading challenges is the aim of a new startup, MosaicML, that just came out of stealth... Read more…

MLPerf Issues New Inferencing Results, Adds Power Metrics, Nvidia Wins (Again)

April 21, 2021

MLPerf.org, the young ML benchmarking organization, today issued its third round of inferencing results (MLPerf Inference v1.0) intended to compare how well var Read more…

IBM’s Prototype Low-Power 7nm AI Chip Offers ‘Precision Scaling’

February 23, 2021

IBM has released details of a prototype AI chip geared toward low-precision training and inference across different AI model types while retaining model quality within AI applications. In a paper delivered during this year’s International Solid-State Circuits Virtual Conference, IBM... Read more…

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Whitepaper

Porting CUDA Applications to Run on AMD GPUs

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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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