high performance computing on graphics processing units: hgpu.org

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Implementation Techniques for SPMD Kernels on CPUs

Joachim Meyer, Aksel Alpay, Sebastian Hack, Holger Fröning, Vincent Heuveline

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Package, performance portability

June 4, 2023 by hgpu

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

Zhuren Liu, Shouzhe Zhang, Justin Garrigus, Hui Zhao

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Tags: Benchmarking, Bioinformatics, Biology, Computer science, CUDA, Genomics, nVidia, nVidia GeForce RTX 3070, Package

May 28, 2023 by hgpu

Experiences Migrating CUDA to SYCL: A Molecular Docking Case Study

Leonardo Solis-Vasquez, Edward Mascarenhas, Andreas Koch

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Tags: Chemistry, Computer science, CUDA, molecular docking, nVidia, nVidia A100, oneAPI, Package, SYCL

May 28, 2023 by hgpu

Communication-minimizing Asynchronous Tensor Parallelism

Siddharth Singh, Zack Sating, Abhinav Bhatele

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Tags: Computer science, CUDA, GPU cluster, Neural networks, nVidia, nVidia A100

May 28, 2023 by hgpu

ACRoBat: Optimizing Auto-batching of Dynamic Deep Learning at Compile Time

Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry

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Tags: Code generation, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce RTX 3070

May 28, 2023 by hgpu

An Asynchronous Dataflow-Driven Execution Model For Distributed Accelerator Computing

Philip Salzmann, Fabian Knorr, Peter Thoman, Philipp Gschwandtner, Biagio Cosenza, Thomas Fahringer

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Tags: Benchmarking, Computer science, CUDA, GPU cluster, MPI, nVidia, nVidia V100, Package, SYCL

May 21, 2023 by hgpu

Improving Energy Efficiency of Basic Linear Algebra Routines on Heterogeneous Systems with Multiple GPUs

Hadi Zamani Sabzi

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Factorization, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 1660, nVidia GeForce GTX 980, Thesis

May 21, 2023 by hgpu

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

Zhiyi Zhang, Pengfei Zhang, Qi Wang

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Java, nVidia, nVidia GeForce RTX 3060 Ti, Package

May 21, 2023 by hgpu

Descend: A Safe GPU Systems Programming Language

Bastian Köpcke, Sergei Gorlatch, Michel Steuwer

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Tags: Computer science, CUDA, nVidia, OpenCL, Package, Programming Languages, Tesla P100

May 14, 2023 by hgpu

Prediction of Performance and Power Consumption of GPGPU Applications

Gargi Alavani, Santonu Sarkar

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Tags: Computer science, CUDA, Energy-efficient computing, Java, Machine learning, nVidia, Package, Performance, PTX, Tesla K20, Thesis

May 14, 2023 by hgpu

Dynamically Finding Optimal Kernel Launch Parameters for CUDA Programs

Taabish Jeshani

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce RTX 2070, Package, Performance, Thesis

May 7, 2023 by hgpu

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

Yanwen Xu, Ang Li, Tyler Sorensen

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Tags: Benchmarking, Computer science, CUDA, FPGA, Heterogeneous systems, HLS, Intel UHD 630, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson Nano, Package, Performance, SYCL

May 7, 2023 by hgpu

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

KISim: Kubernetes Intelligent Scheduling Simulator

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

exa-AMD: Exascale Accelerated Materials Discovery

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

No More Shading Languages: Compiling C++ to Vulkan Shaders

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high performance computing on graphics processing units: hgpu.org

Implementation Techniques for SPMD Kernels on CPUs

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

Experiences Migrating CUDA to SYCL: A Molecular Docking Case Study

Communication-minimizing Asynchronous Tensor Parallelism

ACRoBat: Optimizing Auto-batching of Dynamic Deep Learning at Compile Time

An Asynchronous Dataflow-Driven Execution Model For Distributed Accelerator Computing

Improving Energy Efficiency of Basic Linear Algebra Routines on Heterogeneous Systems with Multiple GPUs

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

Descend: A Safe GPU Systems Programming Language

Prediction of Performance and Power Consumption of GPGPU Applications

Dynamically Finding Optimal Kernel Launch Parameters for CUDA Programs

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

Recent source codes

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

KISim: Kubernetes Intelligent Scheduling Simulator

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

exa-AMD: Exascale Accelerated Materials Discovery

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

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