Newcomer Conduit Leverages Frontera to Understand SARS-CoV-2 ‘Budding’

January 10, 2022

Conduit, created by MIT graduate (and current CEO) Ryan Robinson, was founded in 2017. But it might not have been until a few years later, when the pandemic started, that Conduit may have found its true calling. While Conduit’s commercial division is busy developing a Covid-19 test called nanoSPLASH, its nonprofit arm was granted access to... Read more…

Erik Lindahl on Bio-Research Advances, the March to Mixed-Precision and AI-HPC Synergies

June 8, 2017

At PRACEdays in Barcelona, HPCwire had the opportunity to interview Dr. Erik Lindahl, Stockholm University biophysics professor and chair of the PRACE Scientific Steering Committee about the goals of PRACE, the evolution of PRACEdays, and the latest bioscience and computing trends. 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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Sponsored by AMD

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.

This paper describes how Quanta Cloud Technology (QCT), a long-time Intel® partner, developed the Taiwania 2 and Taiwania 3 supercomputers to meet the research needs of the Taiwan’s academic, industrial, and enterprise users. The Taiwan National Center for High-Performance Computing (NCHC) selected QCT for their expertise in building HPC/AI supercomputers and providing worldwide end-to-end support for solutions from system design, through integration, benchmarking and installation for end users and system integrators to ensure customer success.

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Sponsored by QCT

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