high performance computing on graphics processing units: hgpu.org

hgpu.org » Benchmarking

Orchestration by approximation: mapping stream programs onto multicore architectures

Sardar M. Farhad, Yousun Ko, Bernd Burgstaller, Bernhard Scholz

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Tags: Algorithms, Benchmarking, Compilers, Computer science, Optimization, Performance, Programming Languages

September 23, 2011 by hgpu

Quantifying NUMA and contention effects in multi-GPU systems

Kyle Spafford, Jeremy S. Meredith, Jeffrey S. Vetter

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla M2070

September 23, 2011 by hgpu

Reducing branch divergence in GPU programs

Tianyi David Han, Tarek S. Abdelrahman

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

September 22, 2011 by hgpu

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

Ashwin Prasad, Jayvant Anantpur, R. Govindarajan

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Tags: Benchmarking, Clustering, Computer science, CUDA, Data parallelism, Flow analysis, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTS, Optimization

September 20, 2011 by hgpu

SRAM-DRAM hybrid memory with applications to efficient register files in fine-grained multi-threading

Wing-kei S. Yu, Ruirui Huang, Sarah Q. Xu, Sung-En Wang, Edwin Kan, G. Edward Suh

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Tags: Benchmarking, Computer science, Memory, nVidia, Performance

September 20, 2011 by hgpu

CuMAPz: a tool to analyze memory access patterns in CUDA

Yooseong Kim, Aviral Shrivastava

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Tags: Analytical model, Benchmarking, Computer science, CUDA, Memory, nVidia, Performance, Tesla C1060

September 20, 2011 by hgpu

Stream computing on graphics hardware

Ian Buck

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Tags: Algorithms, ATI, ATI Radeon X800 XT, Benchmarking, Brook, Compilers, Computer science, nVidia, nVidia GeForce 6800, Review, Thesis

September 19, 2011 by hgpu

Fast Mersenne prime testing on the GPU

Andrew Thall

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Tags: Algorithms, Benchmarking, CUDA, Mathematical Software, Mathematics, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Tesla C2050

September 15, 2011 by hgpu

Task superscalar: using processors as functional units

Yoav Etsion, Alex Ramirez, Rosa M. Badia, Eduard Ayguade, Jesus Labarta, Mateo Valero

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Tags: Benchmarking, Cell processor, Computer science, Performance, Programming techniques

September 12, 2011 by hgpu

Task Superscalar: An Out-of-Order Task Pipeline

Yoav Etsion, Felipe Cabarcas, Alejandro Rico, Alex Ramirez, Rosa M. Badia, Eduard Ayguade, Jesus Labarta, Mateo Valero

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Tags: Benchmarking, Cell processor, Computer science, Performance, Programming techniques

September 11, 2011 by hgpu

TimeGraph: GPU scheduling for real-time multi-tasking environments

Shinpei Kato, Karthik Lakshmanan, Ragunathan Rajkumar, Yutaka Ishikawa

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Source codes

Tags: Benchmarking, Computer science, nVidia, nVidia GeForce 9800 GT, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenGL, Operating systems, Package, Real-time graphics, Task scheduling

September 11, 2011 by hgpu

Software-based branch predication for AMD GPUs

Ryan Taylor, Xiaoming Li

Tags: ATI, Benchmarking, Computer science, Performance, Programming techniques

September 11, 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

Orchestration by approximation: mapping stream programs onto multicore architectures

Quantifying NUMA and contention effects in multi-GPU systems

Reducing branch divergence in GPU programs

Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

SRAM-DRAM hybrid memory with applications to efficient register files in fine-grained multi-threading

CuMAPz: a tool to analyze memory access patterns in CUDA

Stream computing on graphics hardware

Fast Mersenne prime testing on the GPU

Task superscalar: using processors as functional units

Task Superscalar: An Out-of-Order Task Pipeline

TimeGraph: GPU scheduling for real-time multi-tasking environments

Software-based branch predication for AMD GPUs

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

Most viewed papers (last 30 days)