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Heterogeneous Computing and Grid Scheduling with Hierarchically Parallel Evolutionary Algorithms

Jinglian Wang, Bin Gong, Hong Liu, Shaohui Li, Juan Yi

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Tags: Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, Task scheduling

April 29, 2014 by hgpu

Multi-GPU Implementation of the Minimum Volume Simplex Analysis Algorithm for Hyperspectral Unmixing

Alexander Agathos, Jun Li, Dana Petcu, Antonio Plaza

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Tags: Algorithms, Computer science, CUDA, GPU cluster, nVidia, Sensing, Tesla M2070

April 29, 2014 by hgpu

A GPU Accelerated Simulator for CO2 Storage

Elisabeth K Prestegard

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Tags: Computer science, CUDA, Finite volume method, nVidia, nVidia GeForce GT 218, Physics, Thesis

April 29, 2014 by hgpu

Piko: A Design Framework for Programmable Graphics Pipelines

Anjul Patney, Stanley Tzeng, Kerry A. Seitz Jr., John D. Owens

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Tags: 3D Graphics and Realism, Code generation, Computer science, nVidia, nVidia GeForce GTX 680, OpenCL, PTX, Rasterization, Raytracing, Rendering

April 29, 2014 by hgpu

On the Use of Remote GPUs and Low-Power Processors for the Acceleration of Scientific Applications

A. Castello, J. Duato, R. Mayo, A. J. Pena, E. S. Quintana-Orti, V. Roca, F. Silla

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Tags: Bioinformatics, Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, Molecular dynamics, nVidia, nVidia GeForce GTX 480, Virtualization

April 27, 2014 by hgpu

Efficient Acceleration of Mutual Information Computation for Nonrigid Registration using CUDA

Kei Ikeda, Fumihiko Ino, Kenichi Hagihara

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Tags: CUDA, Image processing, Image registration, nVidia, nVidia GeForce GTX 580, Package

April 27, 2014 by hgpu

Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures

Hartwig Anzt, Dimitar Lukarski, Stanimire Tomov, Jack Dongarra

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Intel Xeon Phi, Linear Algebra, nVidia, OpenCL, Tesla K40

April 27, 2014 by hgpu

Scattering Parameters and Surface Normals from Homogeneous Translucent Materials using Photometric Stereo

Bo Dong, Kathleen D. Moore, Weiyi Zhang, Pieter Peers

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 660 Ti, Rendering

April 27, 2014 by hgpu

Cellular GPU Models to Euclidean Optimization Problems

Naiyu Zhang

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Tags: Algorithms, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 570, Optimization, Self-organizing map, Thesis

April 27, 2014 by hgpu

On the Parallelization of Integer Polynomial Multiplication

Farnam Mansouri

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Tags: Algorithms, Computer science, CUDA, nVidia, Package, Symbolic Computation, Tesla C2050, Thesis

April 25, 2014 by hgpu

A new way in few-body scattering calculations: discretized Faddeev equations solved on GPU

V.N. Pomerantsev, V.I. Kukulin, O.A. Rubtsova

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Tags: CUDA, Nuclear Theory, nVidia, nVidia GeForce GTX 670, Physics

April 25, 2014 by hgpu

Integrating multi-threading and accelerators into DUNE-ISTL

Steffen Muthing, Dirk Ribbrock, Dominik Goddeke

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, MPI, nVidia, Partial differential equations, PDEs, Tesla C2070

April 25, 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

Applications

Heterogeneous Computing and Grid Scheduling with Hierarchically Parallel Evolutionary Algorithms

Multi-GPU Implementation of the Minimum Volume Simplex Analysis Algorithm for Hyperspectral Unmixing

A GPU Accelerated Simulator for CO2 Storage

Piko: A Design Framework for Programmable Graphics Pipelines

On the Use of Remote GPUs and Low-Power Processors for the Acceleration of Scientific Applications

Efficient Acceleration of Mutual Information Computation for Nonrigid Registration using CUDA

Self-Adaptive Multiprecision Preconditioners on Multicore and Manycore Architectures

Scattering Parameters and Surface Normals from Homogeneous Translucent Materials using Photometric Stereo

Cellular GPU Models to Euclidean Optimization Problems

On the Parallelization of Integer Polynomial Multiplication

A new way in few-body scattering calculations: discretized Faddeev equations solved on GPU

Integrating multi-threading and accelerators into DUNE-ISTL

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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