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NCSA’s Bill Gropp Digs into MPI – Past, Present, and Future
May 18, 2023
If you work in scientific computing, MPI (message passing interface) is likely a part of your life. It may be hidden underneath the applications you run or you Read more…
What’s New in HPC Research: Galaxies, Fugaku, Electron Microscopes & More
January 25, 2021
In this regular feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programmin Read more…
Azure Scaled to Record 86,400 Cores for Molecular Dynamics
November 20, 2020
A new record for HPC scaling on the public cloud has been achieved on Microsoft Azure. Led by Dr. Jer-Ming Chia, the cloud provider partnered with the Beckman I Read more…
Containers as ‘Tupperware’: Experts Debate Container Concepts, Strategies
April 24, 2019
Panels tend to be among the livelier conference sessions and the “Containers” panel at Tabor’s Advanced Scale Forum last week in Jacksonville, Fla., was c Read more…
MPI Is 25 Years Old!
May 1, 2017
Has it really been 25 years since the Message Passing Interface standard was born? It has indeed, and at this year's EuroMPI meeting in September in Chicago, a Read more…
HPC Technique Propels Deep Learning at Scale
February 21, 2017
Researchers from Baidu's Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural networ Read more…
MPI Is Not Perfect … Yet
August 3, 2016
The Message Passing Interface (MPI) is the standard definition of a communication API that has underpinned traditional HPC for decades. The message passing programming represents distributed-memory hardware architectures using processes that send messages to each other. When first standardised in 1993-4, MPI was a major step forward from the many proprietary, system-dependent, and semantically different message-passing libraries that came before it. Read more…
Nielsen and Intel Migrate HPC Efficiency and Data Analytics to Big Data
May 16, 2016
Nielsen has collaborated with Intel to migrate important pieces of HPC technology into Nielsen’s big-data analytic workflows including MPI, mature numerical libraries from NAG (the Numerical Algorithms Group), as well as custom C++ analytic codes. This complementary hybrid approach integrates the benefits of Hadoop data management and workflow scheduling with an extensive pool of HPC tools and C/C++ capabilities for analytic applications. In particular, the use of MPI reduces latency, permits reuse of the Hadoop servers, and co-locates the MPI applications close to the data. Read more…
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