high performance computing on graphics processing units: hgpu.org

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Application Synthesis and Optimization on Heterogeneous Parallel Processing Systems

Chih-Sheng Lin

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTS 250, nVidia GeForce GTX 690, OpenCL, Task scheduling, Tesla C2050, Thesis

December 1, 2014 by hgpu

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

G.R. Mudalige, I.Z. Reguly, M.B. Giles, A.C. Mallinson, W.P. Gaudin, J.A. Herdman

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Tags: Code generation, Computer science, CUDA, GPU cluster, MPI, nVidia, OpenACC, OpenCL, Tesla K20

December 1, 2014 by hgpu

Code Generation Compiler for the OpenMP 4.0 Accelerator Model onto OMPSS

Guray Ozen

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Tesla M2090, Thesis

November 29, 2014 by hgpu

A CUDA implementation of the High Performance Conjugate Gradient benchmark

Everett Phillips, Massimiliano Fatica

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Tesla K20

November 29, 2014 by hgpu

Runtime Comparison of CPU and GPU Using Portable Programming Models

Franz Wiesinger, Florian Nairz, Michael Bogner

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 680, OpenCL, Sorting

November 29, 2014 by hgpu

Improving GPU Performance by Regrouping CPU-Memory Data

Deepthi Gummadi

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Tags: ARM, Computer science, CUDA, nVidia, Performance, Tesla C2075, Tesla K20, Thesis

November 25, 2014 by hgpu

Anisotropic interfacial tension, contact angles, and line tensions: A graphics-processing-unit-based Monte Carlo study of the Ising model

Benjamin J. Block, Suam Kim, Peter Virnau, Kurt Binder

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Tags: Computational Physics, CUDA, Ising model, nVidia, OpenCL, Physics

November 25, 2014 by hgpu

Ageing at the Spin-Glass/Ferromagnet Transition: Monte Carlo Simulation using GPUs

Markus Manssen, Alexander K. Hartmann

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Tags: Condensed matter, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 570, Physics, Statistical Mechanics

November 25, 2014 by hgpu

Scalable Verification Techniques for Data-Parallel Programs

Nathan Yong Seng Chong

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Tags: ARM, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 570, OpenCL, Package, Tesla M2050, Thesis

November 25, 2014 by hgpu

A GPU-based framework for efficient image processing

Per Karlsson

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Tags: CUDA, GLSL, Image processing, nVidia, nVidia GeForce GTX 760, OpenCL, OpenGL, Python, Thesis

November 20, 2014 by hgpu

Using CUDA architecture for computer simulations of thermomechanical phenomena

Grzegorz Michalski, Norbert Sczygiol, Siergiei Leonov

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 200, Solidification

November 20, 2014 by hgpu

Using Graphics Processing Units to solve the classical N-body problem in physics and astrophysics

Mario Spera

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Tags: Astrophysics, CUDA, Electrodynamics, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce GTX Titan, OpenCL, Package, QCD

November 20, 2014 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

Application Synthesis and Optimization on Heterogeneous Parallel Processing Systems

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

Code Generation Compiler for the OpenMP 4.0 Accelerator Model onto OMPSS

A CUDA implementation of the High Performance Conjugate Gradient benchmark

Runtime Comparison of CPU and GPU Using Portable Programming Models

Improving GPU Performance by Regrouping CPU-Memory Data

Anisotropic interfacial tension, contact angles, and line tensions: A graphics-processing-unit-based Monte Carlo study of the Ising model

Ageing at the Spin-Glass/Ferromagnet Transition: Monte Carlo Simulation using GPUs

Scalable Verification Techniques for Data-Parallel Programs

A GPU-based framework for efficient image processing

Using CUDA architecture for computer simulations of thermomechanical phenomena

Using Graphics Processing Units to solve the classical N-body problem in physics and astrophysics

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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