The Deep500 – Researchers Tackle An HPC Benchmark For Deep Learning

How do you know if an HPC system, particularly a larger-scale system, is well-suited for deep learning workloads? Today, that’s not an easy question to answer in the sense there is no widely agreed-upon benchmark or reference architecture for comparing DL performance across systems. A group of researchers led by Tal Ben-Nun and Torsten Hoefler of ETH Zurich has set out to develop Deep500 – a benchmarking suite, reference architecture, and, yes, contest – to provide a meaningful assessment tool for deep learning capabilities on HPC platforms. READ MORE ON: HPC WIRE

Yusra Hamid