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GPU Computing in Economics

Eric M. Aldrich

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Tags: CUDA, Finance, nVidia, Package, Review, Tesla C2075

July 20, 2013 by hgpu

Early Experiences With The OpenMP Accelerator Model

Chunhua Liao, Yonghong Yan, Bronis R. de Supinski, Daniel J. Quinlan, Barbara Chapman

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Package, Tesla K20

July 17, 2013 by hgpu

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

Dmitry Mikushin, Nikolay Likhogrud, Eddy Zheng Zhang, Christopher Bergstrom

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Tags: Code generation, Compilers, Computer science, CUDA, Fortran, nVidia, OpenACC, Package, PTX, Tesla K20

July 15, 2013 by hgpu

The CUDA Handbook: A Comprehensive Guide to GPU Programming

Nicholas Wilt

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Tags: Book, Computer science, CUDA, Image processing, N-body simulation, nVidia, Overview, Package

July 13, 2013 by hgpu

Parallel Graph Processing on Graphics Processors Made Easy

Jianlong Zhong, Bingsheng He

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Package, Tesla C2050

July 12, 2013 by hgpu

ParadisEO-MO-GPU: a Framework for Parallel GPU-based Local Search Metaheuristics

Nouredine Melab, The van Luong, Karima Boufaras, El-Ghazali Talbi

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 480, Package, Performance, Search

July 8, 2013 by hgpu

CrowdCL: Web-Based Volunteer Computing with WebCL

Tommy MacWilliam, Cris Cecka

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Tags: Computer science, Distributed computing, Java, nVidia, nVidia GeForce GT 320 M, OpenCL, Package, Tesla K20

July 7, 2013 by hgpu

A minimal model for acoustic forces on Brownian particles

F. Balboa Usabiaga, R. Delgado-Buscalioni

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Tags: Condensed matter, CUDA, Finite volume method, nVidia, Package, Soft Condensed Matter

July 3, 2013 by hgpu

Computing Strongly Connected Components with CUDA

Miroslav Stuhl

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Thesis

July 3, 2013 by hgpu

vSMC: Parallel Sequential Monte Carlo in C++

Yan Zhou

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Tags: Algorithms, Bayesian, Mathematical Software, Mathematics, nVidia, nVidia Quadro FX 2000, OpenCL, Package, Physics, Signal processing, Statistics

July 1, 2013 by hgpu

Intel Xeon Phi Coprocessor High-Performance Programming

Jim Jeffers, James Jeffers, James Reinders

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Tags: Book, Computer science, Intel, Intel Phi, OpenMP, Package, Review

June 30, 2013 by hgpu

Efficient computation of constrained parameterizations on parallel platforms

Theodoros Athanasiadis, Georgios Zioupos, Ioannis Fudos

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Tags: 3D Graphics and Realism, Computer science, nVidia, OpenCL, Package, Tesla C2070

June 29, 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

GPU Computing in Economics

Early Experiences With The OpenMP Accelerator Model

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

The CUDA Handbook: A Comprehensive Guide to GPU Programming

Parallel Graph Processing on Graphics Processors Made Easy

ParadisEO-MO-GPU: a Framework for Parallel GPU-based Local Search Metaheuristics

CrowdCL: Web-Based Volunteer Computing with WebCL

A minimal model for acoustic forces on Brownian particles

Computing Strongly Connected Components with CUDA

vSMC: Parallel Sequential Monte Carlo in C++

Intel Xeon Phi Coprocessor High-Performance Programming

Efficient computation of constrained parameterizations on parallel platforms

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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