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An In-depth Performance Characterization of CPU- and GPU-based DNN Training on Modern Architectures

Ammar Ahmad Awan, Hari Subramoni, Dhabaleswar K. Panda

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Tags: Benchmarking, Caffe, Computer science, CUBLAS, CUDA, Deep learning, Intel Xeon Phi, Machine learning, nVidia, Tela K40, Tesla K80, Tesla P100

December 24, 2017 by hgpu

KTT - Kernel Tuning Toolkit

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KTT - Kernel Tuning Toolkit

Searching CUDA code autotuning spaces with hardware performance counters: data from benchmarks running on various GPU architectures

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Transparent FPGA Acceleration with TensorFlow

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triSYCL for Xilinx FPGA

AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning

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Efficient MPI-based Communication for GPU-Accelerated Dask Applications

Text2Gestures: A Transformer-Based Network for Generating Emotive Body Gestures for Virtual Agents

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high performance computing on graphics processing units: hgpu.org

An In-depth Performance Characterization of CPU- and GPU-based DNN Training on Modern Architectures

Recent source codes

KTT - Kernel Tuning Toolkit

UPC++: a PGAS library for C++

cuFINUFFT: a load-balanced GPU library for general-purpose nonuniform FFTs

KTT - Kernel Tuning Toolkit

HSA-on-FPGA

SYCL for Vitis 2020.1: experimental melting pot with Intel oneAPI DPC++ SYCL and triSYCL for Xilinx FPGA

AutoFreeze: Automatically Freezing Model Blocks to Accelerate Fine-tuning

C-for-Metal: High Performance SIMD Programming on Intel GPUs

Efficient MPI-based Communication for GPU-Accelerated Dask Applications

Text2Gestures: A Transformer-Based Network for Generating Emotive Body Gestures for Virtual Agents

Most viewed papers (last 30 days)

Featured events

9th International Workshop on OpenCL and SYCL, 2021

The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021

International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020