high performance computing on graphics processing units: hgpu.org

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Generative programming methods for parallel partial differential field equation solvers

Daniel Peter Playne

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Tags: Code generation, Computer science, CUDA, Field equations, MPI, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Tesla C2050, Thesis

December 22, 2011 by hgpu

Extending adaptive sparse grids for stochastic collocation to hybrid parallel architectures

Richard K. Archibald, Ralf Deiterding, John Jakeman

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Tags: Computer science, CUDA, Hybrid computing, nVidia, Stochastic simulation, Tesla C2050

December 22, 2011 by hgpu

Solving Quadratic Programming Problems on Graphics Processing Unit

Yunlong Huang, Keck Voon Ling, Simon See

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Tags: Algorithms, Computer science, CUDA, nVidia, Tesla S1070

December 22, 2011 by hgpu

Warp-Level Parallelism: Enabling Multiple Replications In Parallel on GPU

Jonathan Passerat-Palmbach, Jonathan Caux, Pridi Siregar, Claude Mazel, D.R.C.Hill

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Tags: Benchmarking, Computer science, CUDA, nVidia, Stochastic simulation, Tesla C2050, Warp level parallelism

December 21, 2011 by hgpu

Parallel Inference on Structured Data with CRFs on GPUs

Nico Piatkowski, Katharina Morik

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Tags: Algorithms, Computer science, CUDA, Databases, Graph theory, nVidia, Package, Tesla C2050

December 21, 2011 by hgpu

Implementation of a Parallel Tree Method on a GPU

Naohito Nakasato

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Tags: Astrophysics, ATI, ATI IL, ATI Radeon HD 5870, Computational Complexity, Computer science, Galaxy Astrophysics, Instrumentation and Methods for Astrophysics, KD-tree, OpenCL, Optimization, Performance

December 21, 2011 by hgpu

Performance and Quality of Random Number Generators

V. du Preez, M.G.B. Johnson, A. Leist, K.A. Hawick

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Tags: Algorithms, Computer science, CUDA, Monte Carlo simulation, Numerical simulation, nVidia, nVidia GeForce GTX 580, Pseudo-random number generators, Review

December 20, 2011 by hgpu

A Framework for Genetic Algorithms in Parallel Environments

Tomoyuki Hiroyasu, Ryosuke Yamanaka, Masato Yoshimi, Mitsunori Miki

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 250

December 20, 2011 by hgpu

Analysis of GPGPU Platforms Efficiency in General-Purpose Computations

Pavel Kartashev, Vladislavs Nazaruk

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Tags: ATI, ATI Radeon HD 5750, Benchmarking, Computer science, nVidia, nVidia GeForce GT 240, OpenCL, Performance

December 20, 2011 by hgpu

Can CUDA be exposed through web services?

Massimo Becker

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Tags: Computer science, CUDA, Networks, nVidia, OpenCL, Overview, Thesis

December 20, 2011 by hgpu

Parsing in Parallel on Multiple Cores and GPUs

Mark Johnson

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Tags: Algorithms, Computer science, CUDA, nVidia, Tesla S2050

December 20, 2011 by hgpu

The Future in Mobile Multicore Computing

Blake Hurd, Chiu C. Tan, Jie Wu

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Tags: Computer science, Hardware Architecture, Performance

December 20, 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

Generative programming methods for parallel partial differential field equation solvers

Extending adaptive sparse grids for stochastic collocation to hybrid parallel architectures

Solving Quadratic Programming Problems on Graphics Processing Unit

Warp-Level Parallelism: Enabling Multiple Replications In Parallel on GPU

Parallel Inference on Structured Data with CRFs on GPUs

Implementation of a Parallel Tree Method on a GPU

Performance and Quality of Random Number Generators

A Framework for Genetic Algorithms in Parallel Environments

Analysis of GPGPU Platforms Efficiency in General-Purpose Computations

Can CUDA be exposed through web services?

Parsing in Parallel on Multiple Cores and GPUs

The Future in Mobile Multicore Computing

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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