Introduction I’m going to continue my description of the CIFAR10 benchmark, from where I left off. Related articles Mar 7, 2018 Benchmarks on MATRIX MULTIPLICATION | A comparison between AMD Vega and NVIDIA GeForce series Mar 20, 2018 Benchmarks on MATRIX MULTIPLICATION | TitanV TensorCore (FP16=>FP32) CIFAR10 Average examples pre second Introduction I took the CIFAR10 dataset, which is widely used throughout the world in competitions and benchmarks, and used the public release of TensorFlow in order to measure its training speed.

PLAIDML, which is rumored to be faster than HIP-TENSORFLOW Introduction Hello! HIP-TensorFlow is a library implemented by performing an CUDA simulation of TensorFlow, but since its execution speed is still under development or based on the old TensorFlow, there is a speed difference when compared against the latest NVIDIA + TensorFlow in the DeepLearning. Also, since it works at the same speed for RX 580 as for superior GPUs like Vega 56 and Vega 64, it is still an immature library in that it cannot demonstrate the potential of the Vega series.

Introduction ACUBE Corp. graciously allowed us to borrow a Radeon Pro WX9100, so we have decided to make a report on the card and a record of the results here on our company blog. We would like to extend our heartfelt gratitude to ACUBE Corp. for this opportunity. This report focuses on the Radeon Pro WX9100 card and makes comparisons with the Radeon RX560/580 and RadeonVega56/64/Frontier Edition from the same manufacturer, as well as with the GeForce series from NVIDIA.