high performance computing on graphics processing units: hgpu.org

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Floating-point Mixed-radix FFT Core Generation for FPGA and Comparison with GPU and CPU

Bo Duan, Wendi Wang, Xingjian Li, Chunming Zhang, Peiheng Zhang, Ninghui Sun

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Tags: Algorithms, Computer science, CUDA, FFT, FPGA, nVidia, nVidia GeForce GTX 480, Optimization, Performance

December 20, 2011 by hgpu

Fast Random Graph Generation

Sadegh Heyrani Nobari, Xuesong Lu, Panagiotis Karras, Stephane Bressan

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Tags: Algorithms, Computer science, CUDA, Databases, Graph theory, nVidia, nVidia GeForce 9800 GT, Package

December 19, 2011 by hgpu

GPU-Accelerated Preconditioned Iterative Linear Solvers

Ruipeng Li, Yousef Saad

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Tags: Computer science, Conjugate gradient solver, CUDA, Factorization, Linear Algebra, nVidia, Overview, Sparse matrix, Tesla C1060

December 19, 2011 by hgpu

Optimization of mapped functions sequences using fusions on GPU

Jan Fousek

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Tags: Algorithms, Computer science, CUDA, MPI, nVidia, nVidia GeForce GTX 480, Optimization, Thesis

December 19, 2011 by hgpu

Towards Automatic C Programs Optimization and Parallelization using the PIPS-PoCC Integration

Dounia Khaldi, Corinne Ancourt, Francois Irigoin

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Tags: Benchmarking, Code generation, Computer science, CUDA, FPGA, Heterogeneous systems, MPI, nVidia, OpenMP, Optimization, Package

December 19, 2011 by hgpu

Experiences Developing the OpenUH Compiler and Runtime Infrastructure

Barbara Chapman, Deepak Eachempati, Oscar Hernandez

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Tags: Code generation, Compilers, Computer science, nVidia, Package, PTX

December 19, 2011 by hgpu

Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware

Petr Pospichal, Eoin Murphy, Michael O'Neill, Josef Schwarz, Jiri Jaros

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, Genetic programming, Java, nVidia, nVidia GeForce GTX 480, Optimization

December 19, 2011 by hgpu

Parallel programming with inductive synthesis

Shaon Barman, Rastislav Bodik, Sagar Jain, Yewen Pu, Saurabh Srivastava, Nicholas Tung

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Performance, Programming techniques

December 19, 2011 by hgpu

A Translation Framework for Executing the Sequential Binary Code on CPU/GPU Based Architectures

Erzhou Zhu, Haibing Guan, Guoxing Dong, Yindong Yang, Hongbo Yang

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Tags: Benchmarking, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, PTX

December 18, 2011 by hgpu

Automatic code generation and tuning for stencil kernels on modern shared memory architectures

Matthias Christen, Olaf Schenk, Helmar Burkhart

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Tesla C2050

December 18, 2011 by hgpu

Collision for 75-step SHA-1: Intensive Parallelization with GPU

E.A. Grechnikov, A.V. Adinetz

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Tags: Computer science, nVidia, OpenCL, Package, Security, Tesla M2050, Tesla X2070

December 18, 2011 by hgpu

Leveraging Parallelism with CUDA and OpenCL

S. Park, D. Shires, J. Ross, D. Richie

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Tags: AMD FireStream 9250, ATI, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Programming techniques, Tesla C1060

December 18, 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

Floating-point Mixed-radix FFT Core Generation for FPGA and Comparison with GPU and CPU

Fast Random Graph Generation

GPU-Accelerated Preconditioned Iterative Linear Solvers

Optimization of mapped functions sequences using fusions on GPU

Towards Automatic C Programs Optimization and Parallelization using the PIPS-PoCC Integration

Experiences Developing the OpenUH Compiler and Runtime Infrastructure

Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware

Parallel programming with inductive synthesis

A Translation Framework for Executing the Sequential Binary Code on CPU/GPU Based Architectures

Automatic code generation and tuning for stencil kernels on modern shared memory architectures

Collision for 75-step SHA-1: Intensive Parallelization with GPU

Leveraging Parallelism with CUDA and OpenCL

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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