high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications

DOPA: GPU-based protein alignment using database and memory access optimizations

Laiq Hasan, Marijn Kentie, Zaid Al-Ars

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Tags: Algorithms, Bioinformatics, Biology, Computational Complexity, CUDA, Databases, nVidia, nVidia GeForce GTX 275, Optimization, Package, Sequence alignment, Smith-Waterman algorithm

October 21, 2011 by hgpu

Massively parallel computation using graphics processors with application to optimal experimentation in dynamic control

Sergei Morozov, Sudhanshu Mathur

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Tags: CUDA, Finance, Fortran, Machine learning, nVidia, nVidia GeForce GTX 280, Package

October 21, 2011 by hgpu

Designing the Language Liszt for Building Portable Mesh-based PDE Solvers

Zachary DeVito, Pat Hanrahan

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Package, Partial differential equations, PDEs, Performance, Programming Languages, Tesla C2050

October 19, 2011 by hgpu

AeminiumGPU: A CPU-GPU Hybrid Runtime for the Aeminium Language

Alcides Fonseca

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Tags: Compilers, Computer science, Java, nVidia, nVidia GeForce GTX 285, OpenCL, Optimization, Package, Thesis

October 19, 2011 by hgpu

GPU Parallel Collections For Scala

Kishen Das Kondabagilu Rajanna

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Tags: Compilers, Computer science, CUDA, Java, nVidia, nVidia GeForce 9800 GT, OpenCL, Package, Performance, Thesis

October 19, 2011 by hgpu

Design and Performance of the OP2 Library for Unstructured Mesh Applications

Carlo Bertolli, Adam Betts, Gihan Mudalige, Mike Giles, Paul Kelly

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, OpenCL, OpenMP, Package, Tesla C2050

October 18, 2011 by hgpu

Odeint – Solving ordinary differential equations in C++

Karsten Ahnert, Mario Mulansky

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Tags: Chaotic Dynamics, Computational Physics, Computer science, CUDA, Differential equations, Mathematical Software, nVidia, ODEs, Ordinary differential equations, Package

October 18, 2011 by hgpu

The Anatomy of High-Performance 2D Similarity Calculations

Imran S. Haque, Vijay S. Pande, W. Patrick Walters

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Tags: Algorithms, Biochemistry, Chemistry, Clustering, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Package

October 16, 2011 by hgpu

Physis: An Implicitly Parallel Programming Model for Stencil Computations on Large-Scale GPU-Accelerated Supercomputers

Naoya Maruyama, Tatsuo Nomura, Kento Sato, Satoshi Matsuoka

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Tags: Computer science, CUDA, MPI, nVidia, Optimization, Package, Performance, Programming Languages, Programming techniques, Tesla M2050

October 15, 2011 by hgpu

Accelerating code on multi-cores with FastFlow

Marco Aldinucci, Marco Danelutto, Peter Kilpatrick, Massimiliano Meneghin, Massimo Torquati

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Tags: Computer science, Memory, Package, Performance, Programming techniques

October 15, 2011 by hgpu

Efficient Mapping of Streaming Applications for Image Processing on Graphics Cards

Richard Membarth, Hritam Dutta, Frank Hannig, Jurgen Teich

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Tags: Algorithms, CUDA, Image processing, nVidia, Package, Tesla C1060

October 15, 2011 by hgpu

CudaDMA: Optimizing GPU Memory Bandwidth via Warp Specialization

Michael Bauer, Henry Cook, Brucek Khailany

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Tags: Benchmarking, Computer science, CUDA, Memory model, nVidia, Optimization, Package, Performance, Tesla C2050

October 14, 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

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high performance computing on graphics processing units: hgpu.org

Packages

DOPA: GPU-based protein alignment using database and memory access optimizations

Massively parallel computation using graphics processors with application to optimal experimentation in dynamic control

Designing the Language Liszt for Building Portable Mesh-based PDE Solvers

AeminiumGPU: A CPU-GPU Hybrid Runtime for the Aeminium Language

GPU Parallel Collections For Scala

Design and Performance of the OP2 Library for Unstructured Mesh Applications

Odeint – Solving ordinary differential equations in C++

The Anatomy of High-Performance 2D Similarity Calculations

Physis: An Implicitly Parallel Programming Model for Stencil Computations on Large-Scale GPU-Accelerated Supercomputers

Accelerating code on multi-cores with FastFlow

Efficient Mapping of Streaming Applications for Image Processing on Graphics Cards

CudaDMA: Optimizing GPU Memory Bandwidth via Warp Specialization

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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