high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Parallelization of Mesh Contraction and Fairing using OpenCL

Martin Madaras, Roman Durikovic

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Tags: ATI, ATI Radeon HD 6630 M, Computational Geometry, Computer science, OpenCL, Triangular meshes

May 29, 2013 by hgpu

Effects of Concurrency Techniques and Algorithm Performance: A Comparative Analysis of Single-Threaded, Multi-Threaded, and GPGPU Programming Techniques

Joshua Penton

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Tags: ATI, ATI Radeon HD 6750 M, Computer science, FFT, Java, OpenCL, Package, Performance, Programming techniques

May 28, 2013 by hgpu

Power Modeling and Optimization for GPGPUs

Zhi Li

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Tags: Computer science, GPGPU-sim, Thesis

May 28, 2013 by hgpu

On Leveraging GPUs for Security: discussing k-anonymity and pattern matching

Leonardo Jero

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Tags: Algorithms, ATI, ATI Radeon HD 6850, Computer science, nVidia, nVidia GeForce GT 640, OpenCL, Security, Tesla C2050, Tesla C2070, Thesis

May 28, 2013 by hgpu

Analysis of Parallel Montgomery Multiplication in CUDA

Yuheng Liu

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Tags: Algorithms, Computer science, CUDA, Elliptic curves, nVidia, nVidia GeForce GT 650 M, Security, Thesis

May 28, 2013 by hgpu

Performance Portability in Accelerated Parallel Kernels

John A. Stratton, Hee-Seok Kim, Thoman B. Jablin, Wen-Mei W. Hwu

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Tags: Computer science, Heterogeneous systems, OpenCL, OpenMP, Performance

May 27, 2013 by hgpu

A Performance Modeling and Optimization Analysis Tool for Sparse Matrix-Vector Multiplication on GPUs

Ping Guo, Liqiang Wang, Po Chen

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Tags: Algorithms, Computer science, CUDA, nVidia, Sparse matrix, Tesla C2050

May 27, 2013 by hgpu

Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

Konstantinos Menychtas, Kai Shen, Michael L. Scott

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 670, nVidia Quadro NVS 295, Performance

May 25, 2013 by hgpu

Stencil and Lattice Structures for Field Equation Model Simulations on GPUs

D.P. Playne, K.A. Hawick

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Tags: Code generation, Computer science, CUDA, Field equations, nVidia, nVidia GeForce GTX 580

May 25, 2013 by hgpu

A Tuned, Concurrent-Kernel Approach to Speed Up the APSP Problem

Hector Ortega-Arranz, Yuri Torres, Diego R. Llanos, Arturo Gonzalez-Escribano

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 480

May 25, 2013 by hgpu

On-Demand Generating and Scheduling Optimised Parallel Applications on Heterogeneous Platforms

K. A. Hawick, D. P. Playne

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 580, nVidia GeForce GTX 680, Software Engineering

May 25, 2013 by hgpu

OpenCL Performance Evaluation on Modern Multi Core CPUs

Joo Hwan Lee, Kaushik Patel, Nimit Nigania, Hyojong Kim, Hyesoon Kim

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, OpenCL, Performance

May 25, 2013 by hgpu

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

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Applications

Parallelization of Mesh Contraction and Fairing using OpenCL

Effects of Concurrency Techniques and Algorithm Performance: A Comparative Analysis of Single-Threaded, Multi-Threaded, and GPGPU Programming Techniques

Power Modeling and Optimization for GPGPUs

On Leveraging GPUs for Security: discussing k-anonymity and pattern matching

Analysis of Parallel Montgomery Multiplication in CUDA

Performance Portability in Accelerated Parallel Kernels

A Performance Modeling and Optimization Analysis Tool for Sparse Matrix-Vector Multiplication on GPUs

Enabling OS Research by Inferring Interactions in the Black-Box GPU Stack

Stencil and Lattice Structures for Field Equation Model Simulations on GPUs

A Tuned, Concurrent-Kernel Approach to Speed Up the APSP Problem

On-Demand Generating and Scheduling Optimised Parallel Applications on Heterogeneous Platforms

OpenCL Performance Evaluation on Modern Multi Core CPUs

Recent source codes

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

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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