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StarPU: a Runtime System for Scheduling Tasks over Accelerator-Based Multicore Machines

Cedric Augonnet, Samuel Thibault, Raymond Namyst

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Tags: Computer science, CUDA, Distributed computing, nVidia, nVidia Quadro FX 4600, nVidia Quadro FX 5800, Package, Performance

February 26, 2011 by hgpu

A Tuning Framework for Software-Managed Memory Hierarchies

Manman Ren, Ji Young Park, Mike Houston, Alex Aiken, William J. Dally

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Tags: Algorithms, Cell processor, Compilers, Computer science, Optimization, Performance, Playstation, Programming Languages

February 26, 2011 by hgpu

Real-Time Approaches to Computer Vision

Ron Tal

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Tags: Algorithms, Computer science, Computer vision, CUDA, FPGA, nVidia

February 26, 2011 by hgpu

Believe it or Not! Multi-core CPUs Can Match GPU Performance for FLOP-intensive Application!

Rajesh Bordawekar, Uday Bondhugula, Ravi Rao

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Performance, Programming techniques

February 26, 2011 by hgpu

Concurrent GPU Programming

Lesley Northam

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 M GTX, Programming techniques, Review

February 26, 2011 by hgpu

Handbook of open source tools

Sandeep Koranne

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Tags: Book, Cluster computing, Computer science, CUDA, MPI, nVidia, OpenCL, Pthreads

February 26, 2011 by hgpu

Interactive multiple anisotropic scattering in clouds

Antoine Bouthors, Fabrice Neyret, Nelson Max, Eric Bruneton, Cyril Crassin

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Tags: 3D Graphics and Realism, Algorithms, Computer science, nVidia, nVidia GeForce 8800 GTS

February 25, 2011 by hgpu

OpenGL application live migration with GPU acceleration in personal cloud

Yunbiao Lin, Wei Wang, Kyle Gui

Tags: Algorithms, Computer science, OpenGL, Software Engineering, Virtualization

February 25, 2011 by hgpu

Achieving a single compute device image in OpenCL for multiple GPUs

Jungwon Kim, Honggyu Kim, Joo H. Lee, Jaejin Lee

Tags: Algorithms, Code generation, Compilers, Computer science, CUDA, nVidia, OpenCL, Optimization

February 25, 2011 by hgpu

Statistical Power Consumption Analysis and Modeling for GPU-based Computing

Xiaohan Ma, Mian Dong, Lin Zhong, Zhigang Deng

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 8800 GT

February 24, 2011 by hgpu

Barra, a Modular Functional GPU Simulator for GPGPU

Sylvain Collange, David Defour, David Parello

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9800 GX2, Package, Performance

February 24, 2011 by hgpu

An efficient GPU-based approach for interactive global illumination

Rui Wang, Rui Wang, Kun Zhou, Minghao Pan, Hujun Bao

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Tags: 3D Graphics and Realism, Computer science, KD-tree, nVidia, nVidia GeForce GTX 280, Rendering

February 24, 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

StarPU: a Runtime System for Scheduling Tasks over Accelerator-Based Multicore Machines

A Tuning Framework for Software-Managed Memory Hierarchies

Real-Time Approaches to Computer Vision

Believe it or Not! Multi-core CPUs Can Match GPU Performance for FLOP-intensive Application!

Concurrent GPU Programming

Handbook of open source tools

Interactive multiple anisotropic scattering in clouds

OpenGL application live migration with GPU acceleration in personal cloud

Achieving a single compute device image in OpenCL for multiple GPUs

Statistical Power Consumption Analysis and Modeling for GPU-based Computing

Barra, a Modular Functional GPU Simulator for GPGPU

An efficient GPU-based approach for interactive global illumination

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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