high performance computing on graphics processing units: hgpu.org

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Divergence Analysis and Optimizations

Bruno Coutinho, Diogo Sampaio, Fernando Magno Quintao Pereira, Wagner Meira Jr.

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Optimization, Package, PTX

October 6, 2011 by hgpu

Offloading Java to Graphics Processors

Peter Calvert

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

October 6, 2011 by hgpu

Parallelisation of Java for Graphics Processors

Peter Calvert

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Tags: Algorithms, Benchmarking, Code generation, Computer science, CUDA, Java, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 260, Package, Thesis

October 6, 2011 by hgpu

Performance Analysis and Optimisation of the OP2 Framework on Many-core Architectures

M.B. Giles, G.R. Mudalige, Z. Sharif, G. Markall, P.H.J. Kelly

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Tags: Benchmarking, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 260, OpenMP, Partial differential equations, PDEs, Tesla C2050

October 5, 2011 by hgpu

Parallel Direct Simulation Monte Carlo Computation Using CUDA on GPUs

C.-C. Su, C.-W. Hsieh, M. R. Smith, M. C. Jermy, and J.-S. Wua

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Tags: Benchmarking, Computer science, CUDA, Monte Carlo simulation, nVidia, Tesla C1060

October 5, 2011 by hgpu

Flexible, high performance convolutional neural networks for image classification

Dan C. Ciresan, Ueli Meier, Jonathan Masci, Luca M. Gambardella, Jurgen Schmidhuber

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Tags: Benchmarking, Computer science, CUDA, Image processing, Neural networks, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 580

October 5, 2011 by hgpu

Berkeley Dwarfs on CUDA

Paul Springer

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Tesla C2050, Thesis

October 4, 2011 by hgpu

A Comprehensive Performance Comparison of CUDA and OpenCL

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Cell processor, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, OpenCL, Optimization, Performance

October 1, 2011 by hgpu

Exploring The Latency and Bandwidth Tolerance of CUDA Applications

Gregory Diamos, Sudnya Padalikar

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Tags: Benchmarking, Computer science, CUDA, GPU cluster, Memory, nVidia, Performance, PTX, Tesla C1060

September 30, 2011 by hgpu

Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control

Bo Wu, Eddy Z. Zhang, Xipeng Shen

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Tags: Algorithms, Benchmarking, CMP, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Tesla S1070

September 30, 2011 by hgpu

CBench: Analyzing Compute Performance for Modern NVIDIA and AMD GPUs

Varun Sampath

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Tags: Algorithms, ATI, ATI Radeon HD 6870, Benchmarking, Computer science, CUDA, nVidia, OpenCL, Package, Tesla C2070

September 30, 2011 by hgpu

Many-threaded implementation of differential evolution for the CUDA platform

Pavel Kromer, Vaclav Snasel, Jan Platos, Ajith Abraham

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Differential evolution, Genetic programming, nVidia, Optimization, Tesla C2050

September 29, 2011 by hgpu

AutoDock-GPU: AutoDock for GPUs and other accelerators

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

NCCLX: collective communication framework

Collective Communication for 100k+ GPUs

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

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high performance computing on graphics processing units: hgpu.org

Divergence Analysis and Optimizations

Offloading Java to Graphics Processors

Parallelisation of Java for Graphics Processors

Performance Analysis and Optimisation of the OP2 Framework on Many-core Architectures

Parallel Direct Simulation Monte Carlo Computation Using CUDA on GPUs

Flexible, high performance convolutional neural networks for image classification

Berkeley Dwarfs on CUDA

A Comprehensive Performance Comparison of CUDA and OpenCL

Exploring The Latency and Bandwidth Tolerance of CUDA Applications

Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control

CBench: Analyzing Compute Performance for Modern NVIDIA and AMD GPUs

Many-threaded implementation of differential evolution for the CUDA platform

Recent source codes

AutoDock-GPU: AutoDock for GPUs and other accelerators

NCCLX: collective communication framework

Tutoring LLM into a Better CUDA Optimizer

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

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