high performance computing on graphics processing units: hgpu.org

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From Task-Based GPU Work Aggregation to Stellar Mergers: Turning Fine-Grained CPU Tasks into Portable GPU Kernels

Gregor Daiß, Patrick Diehl, Dominic Marcello, Alireza Kheirkhahan, Hartmut Kaiser, Dirk Pflüger

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Tags: AMD Radeon Instinct MI100, Astrophysics, ATI, CUDA, HIP, nVidia, nVidia A100, Package, performance portability, Physics

October 23, 2022 by hgpu

Towards Performance Portable Programming for Distributed Heterogeneous Systems

Polykarpos Thomadakis, Nikos Chrisochoides

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Package, Performance, performance portability, Tesla V100

October 9, 2022 by hgpu

Performance portability study of epistasis detection using SYCL on NVIDIA GPU

Zheming Jin, Jeffrey S. Vetter

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Tags: Computer science, CUDA, Genomics, nVidia, performance portability, SYCL, Tesla V100

October 9, 2022 by hgpu

Enhancing the Performance Portability of Heterogeneous Circuit Analysis Programs

Tsung-Wei Huang

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Tags: AMD Radeon RX 6900 XT, ATI, Computer science, Deep learning, nVidia, nVidia GeForce RTX 3090, OpenCL, performance portability, PyTorch, SYCL

September 11, 2022 by hgpu

Understanding the Power of Evolutionary Computation for GPU Code Optimization

Jhe-Yu Liou, Muaaz Awan, Steven Hofmeyr, Stephanie Forrest, Carole-Jean Wu

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Tags: Bioinformatics, Biology, Computer science, CUDA, Evolutionary Computations, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 1080 Ti, Package, performance portability, Sequence alignment, Tesla P100, Tesla V100

September 4, 2022 by hgpu

Exploring Thread Coarsening on FPGA

Mostafa Eghbali Zarch, Reece Neff, Michela Becchi

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Tags: Compilers, Computer science, FPGA, OpenCL, Performance, performance portability

August 28, 2022 by hgpu

High-Performance GPU-to-CPU Transpilation and Optimization via High-Level Parallel Constructs

William S. Moses, Ivan R. Ivanov, Jens Domke, Toshio Endo, Johannes Doerfert, Oleksandr Zinenko

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce RTX 2080 Ti, Package, performance portability, Programming Languages

July 10, 2022 by hgpu

Portable, Scalable Approaches for Improving Asynchronous Many-Task Runtime Node Use

John Keith Holmen

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX Titan X, performance portability, Task scheduling

June 5, 2022 by hgpu

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

Benchmarking a Proof-of-Concept Performance Portable SYCL-based Fast Fourier Transformation Library

Vincent R. Pascuzzi, Mehdi Goli

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Tags: AMD Radeon Instinct MI100, ATI, Benchmarking, Computer science, FFT, Heterogeneous systems, HIP, HPC, nVidia, nVidia A100, OpenCL, performance portability, SYCL

March 20, 2022 by hgpu

System-Level Optimization and Code Generation for Graphics Processors using a Domain-Specific Language

Bo Qiao

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Tags: Code generation, Computer science, CUDA, Image processing, Machine learning, nVidia, nVidia GeForce GTX 680, nVidia GeForce RTX 2080, OpenCL, Package, performance portability, Tesla K20, Thesis

January 2, 2022 by hgpu

Achieving near native runtime performance and cross-platform performance portability for random number generation through SYCL interoperability

Vincent R. Pascuzzi, Mehdi Goli

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Tags: AMD Radeon RX Vega 56, ATI, Computer science, Heterogeneous systems, nVidia, nVidia A100, performance portability, Pseudo-random number generators, SYCL

September 19, 2021 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

From Task-Based GPU Work Aggregation to Stellar Mergers: Turning Fine-Grained CPU Tasks into Portable GPU Kernels

Towards Performance Portable Programming for Distributed Heterogeneous Systems

Performance portability study of epistasis detection using SYCL on NVIDIA GPU

Enhancing the Performance Portability of Heterogeneous Circuit Analysis Programs

Understanding the Power of Evolutionary Computation for GPU Code Optimization

Exploring Thread Coarsening on FPGA

High-Performance GPU-to-CPU Transpilation and Optimization via High-Level Parallel Constructs

Portable, Scalable Approaches for Improving Asynchronous Many-Task Runtime Node Use

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

Benchmarking a Proof-of-Concept Performance Portable SYCL-based Fast Fourier Transformation Library

System-Level Optimization and Code Generation for Graphics Processors using a Domain-Specific Language

Achieving near native runtime performance and cross-platform performance portability for random number generation through SYCL interoperability

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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