high performance computing on graphics processing units: hgpu.org

Zachary DeVito, Niels Joubert, Francisco Palacios, Stephen Oakley, Montserrat Medina, Mike Barrientos, Erich Elsen, Frank Ham, Alex Aiken, Karthik Duraisamy, Eric Darve, Juan Alonso, Pat Hanrahan

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Package, Partial differential equations, PDEs, Performance, Programming Languages, Tesla C2050

October 14, 2011 by hgpu

GPU Computing Gems: Jade Edition

Wen-mei W. Hwu

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Tags: Algorithms, Book, Cellular automata, Computational finance, Computer science, Computer vision, CUDA, Finance, Fluid dynamics, Games, GPU cluster, nVidia

October 14, 2011 by hgpu

Towards scalar synchronization in SIMT architectures

Arun Ramamurthy

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Tags: Benchmarking, Computer science, CUDA, nVidia, OpenCL, Performance, Programming techniques, Thesis

October 14, 2011 by hgpu

Fast Multipole Method vs. Spectral Method for the Simulation of Isotropic Turbulence on GPUs

Rio Yokota, L. A. Barba

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Tags: Algorithms, Computational Physics, CUDA, Fast multipole method, FFT, Fluid dynamics, Numerical Analysis, nVidia, Spectral methods, Tesla C2070

October 14, 2011 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

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high performance computing on graphics processing units: hgpu.org

Dymaxion: Optimizing Memory Access Patterns for Heterogeneous Systems

Effects of compression on data intensive algorithms

Bandwidth Reduction Through Multithreaded Compression of Seismic Images

Speeding up the MATLAB complex networks package using graphic processors

Efficient Mapping of Streaming Applications for Image Processing on Graphics Cards

An Analysis of Programmer Productivity versus Performance for High Level Data Parallel Programming

Accelerating Large Scale Image Analyses on Parallel CPU-GPU Equipped Systems

CudaDMA: Optimizing GPU Memory Bandwidth via Warp Specialization

Liszt: A Domain Specific Language for Building Portable Mesh-based PDE Solvers

GPU Computing Gems: Jade Edition

Towards scalar synchronization in SIMT architectures

Fast Multipole Method vs. Spectral Method for the Simulation of Isotropic Turbulence on GPUs

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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