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MLPerf v1.0 Training Benchmarks: Insights into a Record-Setting NVIDIA Performance

Learn about some of the major optimizations made to the NVIDIA platform that contributed to the nearly 7x increase in performance since the first MLPerf… 31 MIN READ
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Accelerating Scientific Applications in HPC Clusters with NVIDIA DPUs Using the MVAPICH2-DPU MPI Library

HPC and AI have driven supercomputers into wide commercial use as the primary data processing engines enabling research, scientific discoveries… 7 MIN READ
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Extending NVIDIA Performance Leadership with MLPerf Inference 1.0 Results

In this post, we step through some of these optimizations, including the use of Triton Inference Server and the A100 Multi-Instance GPU (MIG) feature. 7 MIN READ
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Doubling Network File System Performance with RDMA-Enabled Networking

Network File System (NFS) is a ubiquitous component of most modern clusters. It was initially designed as a work-group filesystem, making a central file store… 4 MIN READ
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Updating AI Product Performance from Throughput to Time-To-Solution

Data scientists and researchers work toward solving the grand challenges of humanity with AI projects such as developing autonomous cars or nuclear fusion… 9 MIN READ
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Building a Benchmark for Human-Level Concept Learning and Reasoning

Humans have an inherent ability to learn novel concepts from only a few samples and generalize these concepts to different situations. Even though today’s… 10 MIN READ