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Efficient Weighted Histogramming on GPUs with CUDA

Mo Xu, Ningyi Xu, Chunshui Zhao, Feng-Hsiung Hsu

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Tags: Computer science, CUDA, Data mining, Machine learning, nVidia, nVidia GeForce GTX 580

January 8, 2013 by hgpu

Alternating Maximization: Unifying Framework for 8 Sparse PCA Formulations and Efficient Parallel Codes

Peter Richtarik, Martin Takac, Selin Damla Ahipasaoglu

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Tags: CUBLAS, CUDA, Machine learning, nVidia, Package, Statistics

December 18, 2012 by hgpu

Scaling High Performance Domain-Specific Language Implementation with Delite

Hassan Chafi

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 275, Thesis

December 10, 2012 by hgpu

Accelerating MapReduce on a coupled CPU-GPU architecture

Linchuan Chen, Xin Huo, Gagan Agrawal

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Tags: APU, ATI, ATI Radeon HD 6550, Computer science, Data mining, Heterogeneous systems, Machine learning, MapReduce, OpenCL

November 20, 2012 by hgpu

Speeding up the evaluation of evolutionary learning systems using GPGPUs

Maria Franco, Natalio Krasnogor, Jaume Bacardit

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Tags: BioHEL, Evolutionary Computations, LCS, Learning Classifier System, Machine learning, Tesla C1060

November 1, 2012 by mariaux

Applying Genetic Algorithms to Tune Heterogeneous Platform Configurations

Max Grossman, Sameer Kulkarni

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Tags: Algorithms, ATI, Computer science, Heterogeneous systems, Machine learning, OpenCL, Optimization

October 9, 2012 by hgpu

Optimising Unstructured Mesh Computational Fluid Dynamics Applications on Multicores via Machine Learning and Code Transformation

Roxana Rusitoru

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Tags: Algorithms, Fluid dynamics, Heterogeneous systems, Machine learning, nVidia, OpenCL, Optimization, Tesla M2050, Thesis

September 28, 2012 by hgpu

Autotuning Wavefront Abstractions for Heterogeneous Architectures

Siddharth Mohanty, Murray Cole

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Tags: ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenCL

September 21, 2012 by hgpu

Evolutionary Clustering on CUDA

Pavel Kromer, Jan Platos, Vaclav Snasel

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Tags: Algorithms, Clustering, Computer science, CUDA, Machine learning, nVidia, Tesla C2050

September 20, 2012 by hgpu

Forecasting high frequency financial time series using parallel FFN with CUDA and ZeroMQ

Paola Arce, Cristian Maureira, Roberto Bonvallet, Cesar Fernandez

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Tags: Algorithms, CUBLAS, CUDA, Finance, Linear Algebra, Machine learning, Neural networks, nVidia, Tesla M2050

September 20, 2012 by hgpu

Massive parallelization of combinatorial statistical genetics analyses porting machine learning methods on general purpose graphics processing units (GPU)

Tony Kam-Thong

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Tags: Biology, CUDA, Genetics, Machine learning, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 580, Package, Thesis

September 16, 2012 by hgpu

GPU-FS-kNN: A Software Tool for Fast and Scalable kNN Computation Using GPUs

Ahmed Shamsul Arefin, Carlos Riveros, Regina Berretta, Pablo Moscato

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Tags: Bioinformatics, Computer science, CUDA, Machine learning, Nearest neighbour, nVidia, Package, Pattern recognition, Tesla C2050

September 5, 2012 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

Efficient Weighted Histogramming on GPUs with CUDA

Alternating Maximization: Unifying Framework for 8 Sparse PCA Formulations and Efficient Parallel Codes

Scaling High Performance Domain-Specific Language Implementation with Delite

Accelerating MapReduce on a coupled CPU-GPU architecture

Speeding up the evaluation of evolutionary learning systems using GPGPUs

Applying Genetic Algorithms to Tune Heterogeneous Platform Configurations

Optimising Unstructured Mesh Computational Fluid Dynamics Applications on Multicores via Machine Learning and Code Transformation

Autotuning Wavefront Abstractions for Heterogeneous Architectures

Evolutionary Clustering on CUDA

Forecasting high frequency financial time series using parallel FFN with CUDA and ZeroMQ

Massive parallelization of combinatorial statistical genetics analyses porting machine learning methods on general purpose graphics processing units (GPU)

GPU-FS-kNN: A Software Tool for Fast and Scalable kNN Computation Using 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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