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A Unified Optimizing Compiler Framework for Different GPGPU Architectures

Yi Yang, Ping Xiang, Jingfei Kong, Mike Mantor, Huiyang Zhou

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Tags: ATI, ATI Radeon HD 5870, Compilers, Computer science, CUBLAS, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL, Optimization, Package, Programming Languages

August 27, 2012 by hgpu

Low-Latency Elliptic Curve Scalar Multiplication

Joppe W. Bos

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Tags: Algorithms, Computer science, CUDA, Elliptic curves, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 465, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Security

August 27, 2012 by hgpu

Scalable Clustering for Vision using GPUs

Wasif Mohiuddin

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Tags: Algorithms, Clustering, Computer science, Computer vision, CUDA, Data mining, nVidia, nVidia GeForce 8600, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Tesla T10, Thesis

August 26, 2012 by hgpu

Coding Ants: Using Ant Colony Optimization to Accelerate CT Reconstruction

Eric Papenhausen, Ziyi Zheng, Klaus Mueller

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

August 22, 2012 by hgpu

Numerical Study of Geometric Multigrid Methods on CPU–GPU Heterogeneous Computers

Chunsheng Feng, Shi Shu, Jinchao Xu, Chen-Song Zhang

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Tags: Computational Physics, CUDA, Differential equations, FFT, Heterogeneous systems, Mathematics, Numerical Analysis, nVidia, nVidia GeForce GTX 480, Partial differential equations, PDEs, Poisson equation

August 22, 2012 by hgpu

Fixing Performance Bugs: An Empirical Study of Open-Source GPGPU Programs

Yi Yang, Ping Xiang, Mike Mantor, Huiyang Zhou

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Tags: ATI, ATI Radeon HD 5870, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL, Performance

August 21, 2012 by hgpu

Shared Memory Multiplexing: A Novel Way to Improve GPGPU Throughput

Yi Yang, Ping Xiang, Mike Mantor, Norm Rubin, Huiyang Zhou

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance

August 21, 2012 by hgpu

Nonmetric Priors for Continuous Multilabel Optimization

Evgeny Strekalovskiy, Claudia Nieuwenhuis, Daniel Cremers

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 480, Optimization

August 17, 2012 by hgpu

vCUDA Framework Development for GPU Virtualization

Aashish Chauhan, Aditya T S, Bakul Mittal, Padmaraj R, Sridutt Nayak

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Virtualization

August 15, 2012 by hgpu

Optimizing the Computation of Eigenvalues Using Graphics Processing Units

Ion Lungu, Alexandru Pirjan, Dana-Mihaela Petrosanu

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Tags: Computer science, CUDA, Linear Algebra, Mathematics, nVidia, nVidia GeForce GTX 480

August 15, 2012 by hgpu

Accelerating cellular automata simulations using AVX and CUDA

Sebastian Szkoda, Zbigniew Koza, Mateusz Tykierko

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Tags: Cellular automata, Computational Physics, Computer science, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 480, Tesla M2075

August 14, 2012 by hgpu

Policy-based Tuning for Performance Portability and Library Co-optimization

Duane Merrill, Michael Garland, Andrew Grimshaw

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce 9800 GTX, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Performance

August 8, 2012 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

A Unified Optimizing Compiler Framework for Different GPGPU Architectures

Low-Latency Elliptic Curve Scalar Multiplication

Scalable Clustering for Vision using GPUs

Coding Ants: Using Ant Colony Optimization to Accelerate CT Reconstruction

Numerical Study of Geometric Multigrid Methods on CPU–GPU Heterogeneous Computers

Fixing Performance Bugs: An Empirical Study of Open-Source GPGPU Programs

Shared Memory Multiplexing: A Novel Way to Improve GPGPU Throughput

Nonmetric Priors for Continuous Multilabel Optimization

vCUDA Framework Development for GPU Virtualization

Optimizing the Computation of Eigenvalues Using Graphics Processing Units

Accelerating cellular automata simulations using AVX and CUDA

Policy-based Tuning for Performance Portability and Library Co-optimization

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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