high performance computing on graphics processing units: hgpu.org

hgpu.org » Tesla D870

GPUburn: A System to Test and Mitigate GPU Hardware Failures

David Defour, Eric Petit

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Tags: Benchmarking, Computer science, CUDA, Fault tolerance, nVidia, OpenCL, Tesla D870

June 2, 2013 by hgpu

SCGPSim: A fast SystemC simulator on GPUs

Mahesh Nanjundappa, Hiren D. Patel, Bijoy A. Jose, Sandeep K. Shukla

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Tags: Code generation, Computer science, CUDA, High-level Languages, nVidia, Tesla D870

July 8, 2011 by hgpu

Power Consumption of GPUs from a Software Perspective

Sylvain Collange, David Defour, Arnaud Tisserand

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 9800 GX2, Tesla C870, Tesla D870, Tesla T10P

January 7, 2011 by hgpu

Multilevel summation of electrostatic potentials using graphics processing units

David J. Hardy, John E. Stone, Klaus Schulten

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Tags: Chemistry, CUDA, Electrostatics, Molecular dynamics, Molecular modeling, Multilevel summation, nVidia, nVidia GeForce GTX 280, Physics, Tesla C870, Tesla D870

November 2, 2010 by hgpu

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Clava: C/C++ Source-to-Source Tool based on Clang

Challenges and Opportunities in C/C++ Source-To-Source Compilation

gpuLik

Statistical Computing With Graphics Processing Units

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

BAT: A standardized benchmark suite for auto-tuners

Towards a Benchmarking Suite for Kernel Tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

EvoTorch: Scalable Evolutionary Computation in Python

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

See all packages

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high performance computing on graphics processing units: hgpu.org

GPUburn: A System to Test and Mitigate GPU Hardware Failures

SCGPSim: A fast SystemC simulator on GPUs

Power Consumption of GPUs from a Software Perspective

Multilevel summation of electrostatic potentials using graphics processing units

Recent source codes

Clava: C/C++ Source-to-Source Tool based on Clang

gpuLik

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

BAT: A standardized benchmark suite for auto-tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

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