high performance computing on graphics processing units: hgpu.org

Applications

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Improving performance of SYCL applications on CPU architectures using LLVM-directed compilation flow

Pietro Ghiglio, Uwe Dolinsky, Mehdi Goli, Kumudha Narasimhan

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Tags: Computer science, CUDA, nVidia, OpenCL, Performance, performance portability, SYCL

May 1, 2022 by hgpu

Performance Comparison of Different OpenCL Implementations of LBM Simulation on Commodity Computer Hardware

Jelena Tekic, Predrag Tekic, Milos Rackovic

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Tags: AMD Radeon R5 M420, AMD Radeon R5 M430, ATI, cfd, Fluid dynamics, Heterogeneous systems, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 940, nVidia GeForce GTX 960, OpenCL, Performance, Tesla C2070

April 17, 2022 by hgpu

Explicit caching HYB: a new high-performance SpMV framework on GPGPU

Chong Chen

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, Package, Sparse matrix, Tesla V100

April 17, 2022 by hgpu

Performance study on GPU offloading techniques using the Gauss matrix inverse algorithm

Yannik Könneker

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 1080, OpenACC, OpenCL, Package, Performance, Tesla V100, Thesis

April 17, 2022 by hgpu

PM4Py-GPU: a High-Performance General-Purpose Library for Process Mining

Alessandro Berti, Minh Phan Nghia, Wil M.P. van der Aalst

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Tags: Computer science, Databases, nVidia, nVidia GeForce RTX 2080, Package, Python

April 17, 2022 by hgpu

Fast Arbitrary Precision Floating Point on FPGA

Johannes de Fine Licht, Christopher A. Pattison, Alexandros Nikolaos Ziogas, David Simmons-Duffin, Torsten Hoefler

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Tags: Computer science, DSP, FPGA, Matrix multiplication, Package

April 17, 2022 by hgpu

Optimizing Performance and Energy Efficiency in Massively Parallel Systems

Raúl Nozal González

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Tags: AMD Radeon RX 5700 XT, ATI, Computer science, Heterogeneous systems, HPC, nVidia, nVidia GeForce GTX 950, nVidia GeForce GTX Titan X, OpenCL, Package, Performance, SYCL, Tesla K20, Thesis

April 10, 2022 by hgpu

Extending SYCL’s Programming Paradigm with Tensor-based SIMD Abstractions

Wilson Feng, Shucai Yao, Kai Ting Wang, Md Aamir Raihan, Laichun Feng, Chunrong Xu

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Tags: Benchmarking, Computer science, Heterogeneous systems, Matrix multiplication, SYCL

April 10, 2022 by hgpu

Performance Models for Heterogeneous Iterative Programs

Aparna Sasidharan

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla V100

April 10, 2022 by hgpu

Persistent Kernels for Iterative Memory-bound GPU Applications

Lingqi Zhang, Mohamed Wahib, Peng Chen, Jintao Meng, Xiao Wang, Satoshi Matsuoka

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Tags: Computer science, CUDA, nVidia, Package, Stencil computation, Tesla A100, Tesla V100

April 10, 2022 by hgpu

ALPINIST: An Annotation-Aware GPU Program Optimizer

Ömer Sakar, Mohsen Safari, Marieke Huisman, Anton Wijs

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Tags: Computer science, CUDA, nVidia, OpenCL, Optimization, Package

April 10, 2022 by hgpu

Advanced Joins on GPUs

Christos Bellas

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX Titan XP, Package, Thesis

March 27, 2022 by hgpu

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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high performance computing on graphics processing units: hgpu.org

Applications

Improving performance of SYCL applications on CPU architectures using LLVM-directed compilation flow

Performance Comparison of Different OpenCL Implementations of LBM Simulation on Commodity Computer Hardware

Explicit caching HYB: a new high-performance SpMV framework on GPGPU

Performance study on GPU offloading techniques using the Gauss matrix inverse algorithm

PM4Py-GPU: a High-Performance General-Purpose Library for Process Mining

Fast Arbitrary Precision Floating Point on FPGA

Optimizing Performance and Energy Efficiency in Massively Parallel Systems

Extending SYCL’s Programming Paradigm with Tensor-based SIMD Abstractions

Performance Models for Heterogeneous Iterative Programs

Persistent Kernels for Iterative Memory-bound GPU Applications

ALPINIST: An Annotation-Aware GPU Program Optimizer

Advanced Joins on GPUs

Recent source codes

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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