high performance computing on graphics processing units: hgpu.org

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Performance Analysis of GPU Accelerators with Realizable Utilization of Computational Density

Justin Richardson, Alan D. George, Herman Lam

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Tags: Computer science, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GT 240, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Performance, Tesla C1060, Tesla C870

August 3, 2012 by hgpu

Parallelizing flow-accumulation calculations on graphics processing units – From iterative DEM preprocessing algorithm to recursive multiple-flow-direction algorithm

Cheng-Zhi Qin, Lijun Zhan

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Tags: CUDA, Earth and Space Sciences, Geoscience, Graph theory, nVidia, nVidia GeForce GT 330

August 2, 2012 by hgpu

Automated Tool to Generate Parallel CUDA code from a Serial C Code

Akhil Jindal, Nikhil Jindal, Divyashikha Sethia

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce 8400 GS

August 2, 2012 by hgpu

C to Cellular Automata and Execution on CPU, GPU and FPGA

Jens Drieseberg, Christian Siemers

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Tags: Cellular automata, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 580, OpenMP

August 2, 2012 by hgpu

Accelerating Pathology Image Data Cross-Comparison on CPU-GPU Hybrid Systems

Kaibo Wang, Yin Huai, Rubao Lee, Fusheng Wang, Xiaodong Zhang, Joel H. Saltz

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Tags: CUDA, Databases, Image processing, nVidia, nVidia GeForce GTX 580, Tesla M2050

August 2, 2012 by hgpu

A GPU-Computing Approach to Solar Stokes Profile Inversion

Brian J. Harker, Kenneth J. Mighell

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Tags: Astrophysics, CUDA, nVidia, Solar and Stellar Astrophysics, Tesla C1060

August 2, 2012 by hgpu

Interference-driven resource management for GPU-based heterogeneous clusters

Rajat Phull, Cheng-Hong Li, Kunal Rao, Srihari Cadambi, Srimat Chakradhar

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, nVidia, PC cluster, Performance, Tesla C2050

August 1, 2012 by hgpu

GPU merge path: a GPU merging algorithm

Oded Green, Robert McColl, David A. Bader

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Tesla C1060, Tesla C2070

August 1, 2012 by hgpu

New Sparse Matrix Storage Format to Improve The Performance of Total SPMV Time

Neelima Reddy, Raghavendra Prakash, Ram Mohana Reddy

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 470, Sparse matrix

August 1, 2012 by hgpu

High-Level Manipulation of OpenCL-Based Subvectors and Submatrices

Karl Rupp

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Tags: Computer science, Factorization, nVidia, nVidia GeForce GTX 470, OpenCL

August 1, 2012 by hgpu

GPU-Accelerated Non-negative Matrix Factorization for Text Mining

Volodymyr Kysenko, Karl Rupp, Oleksandr Marchenko, Siegfried Selberherr, Anatoly Anisimov

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Tags: Algorithms, ATI, ATI Radeon HD 6970, Computer science, Factorization, Nonnegative matrix factorization, nVidia, nVidia GeForce GTX 470, OpenCL, Text mining

August 1, 2012 by hgpu

accULL: An User-directed Approach to Heterogeneous Programming

Ruyman Reyes, Ivan Lopez, Juan J. Fumero, Francisco de Sande

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Source codes

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Package, Python, Tesla C1060, Tesla C2050

July 31, 2012 by hgpu

Allo: Accelerator Design Language

Dato: A Task-Based Programming Model for Dataflow Accelerators

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

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high performance computing on graphics processing units: hgpu.org

Applications

Performance Analysis of GPU Accelerators with Realizable Utilization of Computational Density

Parallelizing flow-accumulation calculations on graphics processing units – From iterative DEM preprocessing algorithm to recursive multiple-flow-direction algorithm

Automated Tool to Generate Parallel CUDA code from a Serial C Code

C to Cellular Automata and Execution on CPU, GPU and FPGA

Accelerating Pathology Image Data Cross-Comparison on CPU-GPU Hybrid Systems

A GPU-Computing Approach to Solar Stokes Profile Inversion

Interference-driven resource management for GPU-based heterogeneous clusters

GPU merge path: a GPU merging algorithm

New Sparse Matrix Storage Format to Improve The Performance of Total SPMV Time

High-Level Manipulation of OpenCL-Based Subvectors and Submatrices

GPU-Accelerated Non-negative Matrix Factorization for Text Mining

accULL: An User-directed Approach to Heterogeneous Programming

Recent source codes

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

HPC Benchmark Survey

HDM: Home made Diffusion Models

General Matrix Multiplication (GEMM)

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

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