high performance computing on graphics processing units: hgpu.org

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Towards energy efficiency and productivity for decision making in mobile robot navigation

Denisa-Andreea Constantinescu

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Tags: Computer science, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson Nano, nVidia Jetson TX1, nVidia Jetson TX2, OpenCL, Robotics, SYCL

December 11, 2022 by hgpu

Three Contributions to the Theory and Practice of Optimizing Compilers

Linxiao Wang

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Tags: Compilers, Computer science, CUDA, LLVM, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX 760 M, Package, Thesis

December 4, 2022 by hgpu

Fast convolution kernels on pascal GPU with high memory efficiency

Qiong Chang, Masaki Onishi, Tsutomu Maruyama

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Tags: CNN, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, Performance

December 4, 2022 by hgpu

Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism

Xupeng Miao, Yujie Wang, Youhe Jiang, Chunan Shi, Xiaonan Nie, Hailin Zhang, Bin Cui

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Tags: Computer science, CUDA, Databases, Deep learning, nVidia, nVidia Titan RTX, Package

December 4, 2022 by hgpu

User-Driven Online Kernel Fusion for SYCL

Victor Perez, Lukas Sommer, Victor Lomüller, Kumudha Narasimhan, Mehdi Goli

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Tags: Compilers, Computer science, Deep learning, OpenCL, Package, SYCL

November 27, 2022 by hgpu

Design Space Exploration of Concurrency Mapping to FPGAs in Weather and Climate Applications with Xilinx SDSoC OpenCL, SDSoC C++ and Vivad

Moteb Salem Alghamdi

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Tags: Computer science, Design space exploration, FPGA, HLS, HPC, OpenCL, Thesis

November 27, 2022 by hgpu

A Hybrid Multi-GPU Implementation of Simplex Algorithm with CPU Collaboration

Basilis Mamalis, Marios Perlitis

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce RTX 2080 Ti, OpenMP

November 27, 2022 by hgpu

Assessing Opportunities of SYCL and Intel oneAPI for Biological Sequence Alignment

Manuel Costanzo, Enzo Rucci, Carlos García Sánchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: Bioinformatics, Biology, Computational biology, Computer science, CUDA, Heterogeneous systems, Intel, Intel UHD 630, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3090, OpenCL, Sequence alignment, SYCL, Tesla V100

November 27, 2022 by hgpu

Challenges and Techniques for Transparent Acceleration of Unmodified Big Data Applications

Maria Nektaria Xekalaki

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Tags: Benchmarking, Computer science, CUDA, FPGA, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX 1060, nVidia Quadro GP100, OpenCL, Package, Performance, Tesla V100, Thesis

November 20, 2022 by hgpu

Going green: optimizing GPUs for energy efficiency through model-steered auto-tuning

Richard Schoonhoven, Bram Veenboer, Ben van Werkhoven, Kees Joost Batenburg

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia RTX A4000, OpenCL, Package, Tesla A100

November 20, 2022 by hgpu

TorchOpt: An Efficient Library for Differentiable Optimization

Jie Ren, Xidong Feng, Bo Liu, Xuehai Pan, Yao Fu, Luo Mai, Yaodong Yang

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Tags: Computer science, CUDA, Deep learning, Mathematical Software, nVidia, OpenMP, Package, PyTorch

November 20, 2022 by hgpu

Capturing the Memory Topology of GPUs

Dominik Größler

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce 840 M, nVidia GeForce RTX 2080 Ti, nVidia Quadro P 6000, Package, Performance, PTX, Tesla K20, Tesla V100, Thesis

November 13, 2022 by hgpu

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Beehive SPIR-V Toolkit

Experiences in Building a Composable and Functional API for Runtime SPIR-V Code Generation

TorchBench: a collection of open source benchmarks used to evaluate PyTorch performance

TorchBench: Benchmarking PyTorch with High API Surface Coverage

Prediction of Performance and Power Consumption of GPGPU Applications

Descend: an attempt at safe imperative GPU programming

Descend: A Safe GPU Systems Programming Language

Redwood heterogeneous framework

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

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high performance computing on graphics processing units: hgpu.org

Programming

Towards energy efficiency and productivity for decision making in mobile robot navigation

Three Contributions to the Theory and Practice of Optimizing Compilers

Fast convolution kernels on pascal GPU with high memory efficiency

Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism

User-Driven Online Kernel Fusion for SYCL

Design Space Exploration of Concurrency Mapping to FPGAs in Weather and Climate Applications with Xilinx SDSoC OpenCL, SDSoC C++ and Vivad

A Hybrid Multi-GPU Implementation of Simplex Algorithm with CPU Collaboration

Assessing Opportunities of SYCL and Intel oneAPI for Biological Sequence Alignment

Challenges and Techniques for Transparent Acceleration of Unmodified Big Data Applications

Going green: optimizing GPUs for energy efficiency through model-steered auto-tuning

TorchOpt: An Efficient Library for Differentiable Optimization

Capturing the Memory Topology of GPUs

Recent source codes

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

AutoDock for GPUs and other accelerators

spotPython: Sequential Parameter Optimization in Python

Test benchmarks for CELERITY

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Beehive SPIR-V Toolkit

TorchBench: a collection of open source benchmarks used to evaluate PyTorch performance

Prediction of Performance and Power Consumption of GPGPU Applications

Descend: an attempt at safe imperative GPU programming

Redwood heterogeneous framework

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