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AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers

Gleison Souza Diniz Mendonça, Chunhua Liao, Fernando Magno Quintão Pereira

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Tags: Benchmarking, Code generation, Computer science, OpenMP, Package

May 3, 2020 by hgpu

Evaluating FPGA Accelerator Performance with a Parameterized OpenCL Adaptation of the HPCChallenge Benchmark Suite

Marius Meyer, Tobias Kenter, Christian Plessl

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Tags: Benchmarking, Computer science, FPGA, HLS, OpenCL, Package

April 26, 2020 by hgpu

A Study of Single and Multi-device Synchronization Methods in Nvidia GPUs

Lingqi Zhang, Mohamed Wahib, Haoyu Zhang, Satoshi Matsuoka

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia DGX-1, Package, Performance, Tesla P100, Tesla V100

April 19, 2020 by hgpu

Deep Learning for Compilers

Chris Cummins

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Tags: AMD Radeon HD 7970, ATI, Benchmarking, Compilers, Computer science, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX 970, OpenCL, Package, Thesis

April 5, 2020 by hgpu

Performance evaluation of deep learning on smartphones

Abhishek Srivastava

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Tags: Benchmarking, Computer science, Deep learning, TensorFlow, Thesis

March 22, 2020 by hgpu

Automated test generation for OpenCL kernels using fuzzing and constraint solving

Chao Peng, Ajitha Rajan

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Tags: Benchmarking, Computer science, OpenCL, Package

March 15, 2020 by hgpu

Towards Green Computing: A Survey of Performance and Energy Efficiency of Different Platforms using OpenCL

Philip Heinisch, Katharina Ostaszewski, Hendrik Ranocha

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Tags: AMD FirePro S9150, AMD Radeon R9 280X, ARM, ATI, Benchmarking, Computer science, Energy-efficient computing, Heterogeneous systems, nVidia, nVidia GeForce GTX 570, nVidia GRID K520, nVidia Titan RTX, OpenCL, survey, Tesla C2075, Tesla P100, Tesla V100

March 15, 2020 by hgpu

Using Parallel Programming Models for Automotive Workloads on Heterogeneous Systems – a Case Study

Lukas Sommer, Florian Stock, Leonardo Solis-Vasquez, Andreas Koch

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Tags: Automotive, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson TX2, OpenCL, OpenMP

January 26, 2020 by hgpu

A Parallel Sparse Tensor Benchmark Suite on CPUs and GPUs

Jiajia Li, Mahesh Lakshminarasimhan, Xiaolong Wu, Ang Li, Catherine Olschanowsky, Kevin Barker

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Tags: Benchmarking, Computer science, CUDA, Linear Algebra, Machine learning, nVidia, nVidia DGX-1, Package, Performance, Tesla P100, Tesla V100

January 12, 2020 by hgpu

PyTorch: An Imperative Style, High-Performance Deep Learning Library

Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, Soumith Chintala

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia Quadro GP100, Package, Python, PyTorch

December 8, 2019 by hgpu

Benchmarking Deep Learning Models on Jetson TX2

Lucas Pedro Bordignon, Aldo von Wangenheim

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Tags: Artificial intelligence, Benchmarking, Computer science, CUDA, Deep learning, Image recognition, nVidia, nVidia Jetson TX2, Overview, Package, Tutorial

November 24, 2019 by hgpu

Performance Evaluation of Advanced Features in CUDA Unified Memory

Steven W. D. Chien, Ivy B. Peng, Stefano Markidis

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 1050, Package, Prefetch, Tesla V100

October 27, 2019 by hgpu

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

Concurrent Scheduling of High-Level Parallel Programs on Multi-GPU Systems

wgpy: WebGL accelerated numpy-compatible array library for web browser

WgPy: GPU-accelerated NumPy-like array library for web browsers

Microbenchmarking OpenMP target offload with Catch2

A Microbenchmark Framework for Performance Evaluation of OpenMP Target Offloading

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