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MRPB: Memory Request Prioritization for Massively Parallel Processors

Wenhao Jia, Kelly A. Shaw, Margaret Martonosi

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, Performance, Tesla C2050

January 16, 2014 by hgpu

Towards Portable Performance for Explicit Hydrodynamics Codes

A. C. Mallinson, D. A. Beckingsale, W. P. Gaudin, J. A. Herdman, S. A. Jarvis

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Tags: APU, ATI, ATI FirePro V7800, Computer science, Fluid dynamics, MPI, nVidia, OpenCL, Package, Performance, Tesla K20

January 14, 2014 by hgpu

Warp-Level Divergence in GPUs: Characterization, Impact, and Mitigation

Ping Xiang, Yi Yang, Huiyang Zhou

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance

January 12, 2014 by hgpu

Conditional component composition for GPU-based systems

Usman Dastgeer, Christoph W. Kessler

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Tags: Computer science, CUDA, nVidia, Performance, Tesla C2050

January 6, 2014 by hgpu

Accelerating Simulation Codes through the GeMTC Framework

Digvijay Singh Gahlot, Scott Krieder, Ioan Raicu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Performance

January 3, 2014 by hgpu

Efficiency analysis of a physical problem: Different parallel computational approaches for a dynamical integrator evolution

Adriana Gaudiani, Alejandro Soba, M. Florencia Carusela

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Tags: Algorithms, Computer science, CUDA, MPI, nVidia, nVidia GeForce GTX 560 Ti, Performance

December 25, 2013 by hgpu

Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

Tetsuya Odajima, Taisuke Boku, Mitsuhisa Sato, Toshihiro Hanawa, Yuetsu Kodama, Raymond Namyst, Samuel Thibault, Olivier Aumage

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Package, Performance, Task scheduling, Tesla M2090

December 25, 2013 by hgpu

Energy Auto-tuning using the Polyhedral Approach

Wei Wang, John Cavazos, Allan Porterfield

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Tags: Computer science, Intel Xeon Phi, Performance

December 22, 2013 by hgpu

Tesla vs. Xeon Phi vs. Radeon A Compiler Writer’s Perspective

Brent Leback, Douglas Miles, Michael Wolfe

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Tags: ATI, Compilers, Computer science, Intel Xeon Phi, nVidia, OpenCL, Performance, Tesla

December 18, 2013 by hgpu

Data Transfer Matters for GPU Computing

Yusuke Fujii, Takuya Azumi, Nobuhiko Nishio, Shinpei Kato, Masato Edahiro

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Package, Performance

December 13, 2013 by hgpu

Lessons learned from contrasting a BLAS kernel implementations

Andres More

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Tags: BLAS, Computer science, CUDA, nVidia, nVidia Quadro FX 770 M, Performance

December 12, 2013 by hgpu

Integrated GPUs: how useful are they in HPC?

Jonatan Jansson

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Tags: APU, ATI, ATI Radeon HD 6970, Computer science, OpenCL, Performance, Thesis

December 9, 2013 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

MRPB: Memory Request Prioritization for Massively Parallel Processors

Towards Portable Performance for Explicit Hydrodynamics Codes

Warp-Level Divergence in GPUs: Characterization, Impact, and Mitigation

Conditional component composition for GPU-based systems

Accelerating Simulation Codes through the GeMTC Framework

Efficiency analysis of a physical problem: Different parallel computational approaches for a dynamical integrator evolution

Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

Energy Auto-tuning using the Polyhedral Approach

Tesla vs. Xeon Phi vs. Radeon A Compiler Writer’s Perspective

Data Transfer Matters for GPU Computing

Lessons learned from contrasting a BLAS kernel implementations

Integrated GPUs: how useful are they in HPC?

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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