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Unsupervised Asset Cluster Analysis Implemented with Parallel Genetic Algorithms on the NVIDIA CUDA Platform

Dariusz Cieslakiewicz

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Tags: Algorithms, Cluster analysis, Clustering, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 660 M, Thesis

July 18, 2014 by hgpu

GPU acceleration of Runge Kutta-Fehlberg and its comparison with Dormand-Prince method

Wo Mei Seen, R. U. Gobithaasan, Kenjiro T. Miura

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Tags: Algorithms, Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GT 540 M, ODEs, Ordinary differential equations

July 18, 2014 by hgpu

Efficient On-the-fly Category Retrieval using ConvNets and GPUs

Ken Chatfield, Karen Simonyan, Andrew Zisserman

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Tags: Computer science, Computer vision, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX Titan, Pattern recognition

July 18, 2014 by hgpu

Efficient implementation of computationally intensive algorithms on parallel computing platforms

Csaba Nemes

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 570, Tesla K20, Thesis

July 17, 2014 by hgpu

Energy-Efficient Collective Reduce and Allreduce Operations on Distributed GPUs

Lena Oden, Benjamin Klenk, Holger Froning

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Tags: Computer science, CUDA, Distributed computing, Energy-efficient computing, Heterogeneous systems, nVidia, Tesla K20

July 17, 2014 by hgpu

Optimal Periods for Probing Convergence of Infinite-stage Dynamic Programmings on GPUs

Tsutomu Inamoto, Yoshinobu Higami, Shin-ya Kobayashi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Performance

July 17, 2014 by hgpu

GPUdrive: Reconsidering Storage Accesses for GPU Acceleration

Mustafa Shihab, Karl Taht, Myoungsoo Jung

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Storage system

July 16, 2014 by hgpu

Interactive GPU Ray Casting using Progressive Blue Noise Sampling

R. Gmyr, S. Arens, G. Domik

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Tags: Algorithms, Computer science, GLSL, OpenGL, Visualization

July 16, 2014 by hgpu

Parallel Variable Pre-Selection and Lookahead Solving on GPUs

Christopher Schuster

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, Package, SAT

July 16, 2014 by hgpu

CUD@SAT: SAT Solving on GPUs

Alessandro Dal Pal'u, Agostino Dovier, Andrea Formisano, Enrico Pontelli

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Tags: Computer science, CUDA, Numerical simulation, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 560, Package, SAT, Tesla C2075

July 15, 2014 by hgpu

On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

David Rohr

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Review, Thesis

July 14, 2014 by hgpu

A Fine Grained Cycle Sharing System with Cooperative Multitasking on GPUs

Fumihiko Ino, Yosuke Oka, Kenichi Hagihara

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Tags: Computer science, CUDA, Distributed computing, Grid, nVidia, nVidia GeForce GTX 680, Task scheduling

July 14, 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

Unsupervised Asset Cluster Analysis Implemented with Parallel Genetic Algorithms on the NVIDIA CUDA Platform

GPU acceleration of Runge Kutta-Fehlberg and its comparison with Dormand-Prince method

Efficient On-the-fly Category Retrieval using ConvNets and GPUs

Efficient implementation of computationally intensive algorithms on parallel computing platforms

Energy-Efficient Collective Reduce and Allreduce Operations on Distributed GPUs

Optimal Periods for Probing Convergence of Infinite-stage Dynamic Programmings on GPUs

GPUdrive: Reconsidering Storage Accesses for GPU Acceleration

Interactive GPU Ray Casting using Progressive Blue Noise Sampling

Parallel Variable Pre-Selection and Lookahead Solving on GPUs

CUD@SAT: SAT Solving on GPUs

On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

A Fine Grained Cycle Sharing System with Cooperative Multitasking on GPUs

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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