high performance computing on graphics processing units: hgpu.org

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Benchmarking Next Generation Hardware Platforms: An Experimental Approach

Vishakha Gupta, Adit Ranadive, Ada Gavrilovska, Karsten Schwan

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Tags: Benchmarking, CUDA, Finance, Heterogeneous systems, Image processing, nVidia, nVidia GeForce 8800 GTX

March 1, 2012 by hgpu

Customizing Instruction Set Extensible Reconfigurable Processors using GPUs

Unmesh D. Bordoloi, Bharath Suri, Swaroop Nunna, Samarjit Chakraborty, Petru Eles, Zebo Peng

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, OpenCL, Optimization, Tesla M2050

February 10, 2012 by hgpu

Symbolic Testing of OpenCL Code

Peter Collingbourne, Cristian Cadar, Paul H. J. Kelly

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Tags: Benchmarking, Code generation, Computer science, nVidia, OpenCL, Package, PTX, Tesla C1060

February 8, 2012 by hgpu

Verifiable Computation with Massively Parallel Interactive Proofs

Justin Thaler, Mike Roberts, Michael Mitzenmacher, Hanspeter Pfister

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Tags: Benchmarking, Cloud, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 480, Package, Security

February 8, 2012 by hgpu

Realtime scheduling using GPUs – proof of feasibility

Peter Fodrek, Ludovit Farkas, Tomas Murgas

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Tags: Benchmarking, Computer science, nVidia, nVidia GeForce GT 310 M, OpenCL, Task scheduling

January 25, 2012 by hgpu

A High Performance Parallel FDTD Method Enhanced By Using SSE Instruction Set

Dau-Chyrh Chang, Shao-Hsiang Yen, Xiaoling Yang, Lihong Zhang, Wenhua Yu

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Tags: Benchmarking, Electrodynamics, FDTD, Finite difference, Finite-difference time-domain, nVidia, Tesla C1060

January 19, 2012 by hgpu

LNA: Fast Protein Classification Using A Laplacian Characterization of Tertiary Structure

Nicolas Bonnel, Pierre-Francois Marteau

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Tags: Algorithms, Benchmarking, Biology, Databases, nVidia, OpenCL, Tesla M2050

January 18, 2012 by hgpu

Evaluation and enhancement of memory efficiency targeting general-purpose computations on scalable data-parallel GPU architectures

Byunghyun Jang

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, OpenCL, Optimization, Thesis

January 18, 2012 by hgpu

Decreasing NAME III Solution Time Using GP-GPU

Kingsley Gale-Sides

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Tags: Benchmarking, Cloud, Computer science, CUDA, Fortran, MPI, nVidia, Tesla C2050, Tesla M1060, Thesis

January 1, 2012 by hgpu

Comparison of Fragmentation/Dispersion Models for Asteroid Nuclear Disruption Mission Design

Brian D. Kaplinger, Bong Wie

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Tags: Algorithms, Astrophysics, Benchmarking, CUDA, nVidia, Tesla C2050

December 31, 2011 by hgpu

Resource-Aware Compiler Prefetching for Fine-Grained Many-Cores

George C. Caragea, Alexandros Tzannes, Fuat Keceli, Rajeev Barua, Uzi Vishkin

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Tags: Algorithms, ASIC, Benchmarking, Computer science, Memory level parallelism, nVidia, Package, Prefetch

December 29, 2011 by hgpu

Acceleration of PIC Simulation with GPU

Junya Suzuki, Hironori Shimazu, Keiichiro Fukazawa, Mitsue Den

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Tags: Benchmarking, CUDA, nVidia, Particle-in-cell methods, Physics, Plasma physics, Tesla C1060

December 29, 2011 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

Benchmarking Next Generation Hardware Platforms: An Experimental Approach

Customizing Instruction Set Extensible Reconfigurable Processors using GPUs

Symbolic Testing of OpenCL Code

Realtime scheduling using GPUs – proof of feasibility

A High Performance Parallel FDTD Method Enhanced By Using SSE Instruction Set

LNA: Fast Protein Classification Using A Laplacian Characterization of Tertiary Structure

Evaluation and enhancement of memory efficiency targeting general-purpose computations on scalable data-parallel GPU architectures

Comparison of Fragmentation/Dispersion Models for Asteroid Nuclear Disruption Mission Design

Resource-Aware Compiler Prefetching for Fine-Grained Many-Cores

Acceleration of PIC Simulation with GPU

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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