March 8, 2022
Love it or hate it, improv — though it may appear random — is often more purposeful and patterned than it may seem. And, improbable as it may seem, supercom Read more…
November 12, 2021
This year, Penn State launched the NEID (NN-explore Exoplanet Investigations with Doppler spectroscopy) astronomical spectrograph, part of a collaboration betwe Read more…
January 14, 2021
One might not think “aircraft” when picturing the U.S. Navy, but the military branch actually has thousands of aircraft currently in service – and now, su Read more…
November 11, 2020
Doctors use a variety of sensors to monitor a host of bodily functions and metrics that inform patient health, particularly surrounding intensive medical procedures. Nitric oxide (NO) and nitrogen dioxide (NO2) levels are two such metrics, with the former (produced by the human body) relaxing... Read more…
May 6, 2020
Months into the COVID-19 pandemic, supercomputers crunching the coronavirus is the norm, not the exception. Most of these systems are focused on various element Read more…
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.
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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