high performance computing on graphics processing units: hgpu.org

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Massively parallel approximate Gaussian process regression

Robert B. Gramacy, Jarad Niemi, Robin Weiss

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Tags: Cluster computing, CUDA, nVidia, Statistics, Tesla M2090

October 22, 2013 by hgpu

Fingerprint Local Invariant Feature Extraction on GPU with CUDA

Ali Ismail Awad

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Tags: Algorithms, Biometrics, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GT 430, SIFT

October 22, 2013 by hgpu

Solving Multiple Queries through a Permutation Index in GPU

Mariela Lopresti, Natalia Miranda, Fabiana Piccoli, Nora Reyes

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GT 520 M, nVidia GeForce GTX 330 M, nVidia GeForce GTX 550 Ti, Search

October 21, 2013 by hgpu

Concurrent kernel execution on Graphic Processing Units

Adrien Cassagne, Aurelien George, Benjamin Lorendeau, Jean-Charles Papin, Antoine Rougier

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 660, nVidia Quadro 4000, OpenCL, Performance, Thesis

October 21, 2013 by hgpu

Moim: A Multi-GPU MapReduce Framework

Mengjun Xie, Kyoung-Don Kang, Can Basaran

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Tags: Computer science, CUDA, MapReduce, MPI, nVidia, nVidia GeForce GTX 580, Thrust

October 21, 2013 by hgpu

Work Efficient Parallel Algorithms for Large Graph Exploration

Dip Sankar Banerjee, Shashank Sharma, Kishore Kothapalli

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Tags: Algorithms, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, nVidia GeForce GTX 580

October 21, 2013 by hgpu

Architecture-and Workload-Aware Heterogeneous Algorithms for Sparse Matrix Vector Multiplication

Sivaramakrishna Bharadwaj Indarapu, Manoj Maramreddy, Kishore Kothapalli

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, Sparse matrix

October 21, 2013 by hgpu

Multi-Scale Scheduling Techniques for Signal Processing Systems

Zheng Zhou

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Tags: Algorithms, CUDA, DSP, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Particle swarm optimization, Signal processing, Thesis

October 19, 2013 by hgpu

FlexGrip: A Soft GPGPU for FPGAs

Kevin Andryc, Murtaza Merchant, Russell Tessier

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Tags: Computer science, CUDA, FPGA, nVidia

October 19, 2013 by hgpu

An Incompressible Navier-Stokes Equations Solver on the GPU Using CUDA

Niklas Karlsson

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Tags: Algorithms, CUDA, Fluid dynamics, Laplace and Poisson equation, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GTX 660 Ti, Poisson equation, Thesis

October 19, 2013 by hgpu

Massively Parallel Jacobian Computation

Wanqi Li

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Tags: CUDA, Mathematics, nVidia, nVidia GeForce GT 650 M, Package, Thesis

October 19, 2013 by hgpu

Construction of a Virtual Cluster by Integrating PCI Pass-Through for GPU and InfiniBand Virtualization in Cloud

Chao-Tung Yang, Wei-Shen Ou

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Tags: Cloud, Cluster computing, Computer science, CUDA, GPU cluster, nVidia, Tesla C2050, Tesla C2070, Tesla C2075, Tesla K20, Virtualization

October 19, 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

Massively parallel approximate Gaussian process regression

Fingerprint Local Invariant Feature Extraction on GPU with CUDA

Solving Multiple Queries through a Permutation Index in GPU

Concurrent kernel execution on Graphic Processing Units

Moim: A Multi-GPU MapReduce Framework

Work Efficient Parallel Algorithms for Large Graph Exploration

Architecture-and Workload-Aware Heterogeneous Algorithms for Sparse Matrix Vector Multiplication

Multi-Scale Scheduling Techniques for Signal Processing Systems

FlexGrip: A Soft GPGPU for FPGAs

An Incompressible Navier-Stokes Equations Solver on the GPU Using CUDA

Massively Parallel Jacobian Computation

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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