high performance computing on graphics processing units: hgpu.org

Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Yan, Meghan Cowan, Haichen Shen, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

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Tags: Compilers, Computer science, Deep learning, FPGA, Machine learning, nVidia, nVidia GeForce GTX Titan X, Optimization, Package, performance portability

October 13, 2018 by hgpu

Sparse Winograd Convolutional neural networks on small-scale systolic arrays

Feng Shi, Haochen Li, Yuhe Gao, Benjamin Kuschner, Song-Chun Zhu

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Tags: Analytical model, Computer science, Deep learning, FPGA, Neural networks

October 13, 2018 by hgpu

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

HiRep

Scaling SU(2) to 1000 GPUs using HiRep

Gaia AVU-GSR

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

High Performance Computing with FPGAs and OpenCL

Automatic Mapping for OpenCL-Programs on CPU/GPU Heterogeneous Platforms

The Ocean Tensor Package

Towards Efficient Large-Scale Graph Neural Network Computing

Improving OpenCL Performance by Specializing Compiler Phase Selection and Ordering

Using Compiler Snippets to Exploit Parallelism on Heterogeneous Hardware: A Java Reduction Case Study

A Survey of FPGA-based Accelerators for Convolutional Neural Networks

AI Benchmark: Running Deep Neural Networks on Android Smartphones

Exploiting Task Parallelism with OpenCL: A Case Study

Resource Elastic Virtualization for FPGAs using OpenCL

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

Sparse Winograd Convolutional neural networks on small-scale systolic arrays

Recent source codes

tdg-benchs: benchmarks used to test the performance of taskgraph

SW#SYCL

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations