GIGABYTE Technology, an industry leader in high-performance servers and workstations, today announced GIGABYTE as one of the founding members of MLCommons, an open engineering consortium with the goal of accelerating machine learning with benchmarking, large-scale open data sets, and best practices that are community-driven.
In 2018, a group from Google, Baidu, Harvard, and Stanford created a benchmarking suite for machine learning called MLPerf. The purpose was to evaluate the new generation of accelerators to neural-networking jobs performance. By having benchmarking tools, companies and universities would be able to design hardware and software optimized for training and inferencing machine learning workloads.
Now with MLCommons, collaboration across countries, industries, and research institutions into the dynamic field of machine learning can lead to greater progress in healthcare and other industries. GIGABYTE will continue support and use purpose-built servers to help the efforts. MLPerf Inference v0.7 results for datacenter were run with the GIGABYTE G292-Z43 paired with 16 x NVIDIA T4, and the GIGABYTE G482-Z52 with 2 x NVIDIA A100.
“Data-driven decision making has always been a cornerstone in the fields of science and technology, and with the arrival of machine learning, incredibly large amounts of data need to be efficiently processed on platforms suited for it,” said Alan Chen, AVP at GIGABYTE Technology. “We support the efforts of MLCommons based on their mission of inclusion and aim to improve society through discoveries.”
“MLCommons is uniting the industry’s leading experts and academics to develop and share best practices, benchmarks and public data sets that will increase machine learning’s positive impact on society,” said David Kanter, Executive Director at MLCommons. “We’re excited to welcome GIGABYTE as a founding member, and look forward to their support in accelerating innovation in the industry.”
