ORNL Debuts Cumulus-2 Cluster for Climate Data

July 22, 2022

Amid the much-deserved fanfare for the exascale Frontier system at Oak Ridge National Laboratory (ORNL), the lab, in April, launched a much smaller, but more la Read more…

Nvidia Combines Modulus, Omniverse for Earth-2 and Other Digital Twins

March 22, 2022

An accurate digital twin can be a boon to scientific endeavors, from recreating individual buildings in a city to understand energy use to recreating the Earth’s climate system to understand the effects of policies on climate change. At GTC21, Nvidia made waves by announcing that its Modulus framework for physics-based ML models and its... Read more…

US to Triple Its Supercomputing Capacity for Weather and Climate with Two New Crays

February 20, 2020

The blizzard of news around the race for weather and climate supercomputing leadership continues. Just three days after the UK announced a £1.2 billion plan to build the world’s largest weather and climate supercomputer, the U.S. National Oceanic and Atmospheric Administration... Read more…

NOAA Updates Its Massive, Supercomputer-Generated Climate Dataset

January 15, 2020

As Australia burns, understanding and mitigating the climate crisis is more urgent than ever. Now, by leveraging the computing resources at the National Energy Research Scientific Computing Center (NERSC), the U.S. National Oceanic and Atmospheric Administration (NOAA) has updated its 20th Century Reanalysis Project (20CR) dataset... Read more…

Topology Can Help Us Find Patterns in Weather

December 6, 2018

Topology--the study of shapes--seems to be all the rage. You could even say that data has shape, and shape matters. Shapes are comfortable and familiar concepts, so it is intriguing to see that many applications are being recast to use topology. For instance, looking for weather and climate patterns. Read more…

WCRP’s New Strategic Plan for Climate Research Highlights the Importance of HPC

July 19, 2018

As climate modeling increasingly leverages exascale computing and researchers warn of an impending computing gap in climate research, the World Climate Research Programme (WCRP) is developing its new Strategic Plan – and high-performance computing is slated to play a critical role. Read more…

New Exascale System for Earth Simulation Introduced

April 23, 2018

After four years of development, the Energy Exascale Earth System Model (E3SM) will be unveiled today and released to the broader scientific community this mont Read more…

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate 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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