high performance computing on graphics processing units: hgpu.org

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High-accuracy Optimization by Parallel Iterative Discrete Approximation and GPU Cluster Computing

Di Zhao

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Tags: Cluster computing, Computer science, CUDA, GPU cluster, Machine learning, MPI, nVidia, nVidia GeForce GTX 660

September 16, 2014 by hgpu

Machine learning for ultrafast X-ray diffraction patterns on large-scale GPU clusters

Tomas Ekeberg, Stefan Engblom, Jing Liu

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Tags: Algorithms, Biological Physics, Biology, Biomolecules, Cluster computing, Computational Complexity, CUDA, GPU cluster, Machine learning, nVidia, nVidia GeForce GTX 680, OpenMPI

September 16, 2014 by hgpu

A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing

Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen

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Tags: Algorithms, Biology, CUDA, Genetics, Machine learning, Neuroscience, nVidia, nVidia GeForce GTX Titan, Statistics

September 9, 2014 by hgpu

HSApriori: High Speed Association Rule Mining using Apriori Based Algorithm for GPU

D.William Albert, K.Fayaz, D.Veerabhadra Babu

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Tags: Algorithms, Computer science, Data mining, Java, Machine learning, nVidia, OpenCL, Tesla

August 26, 2014 by hgpu

Exploiting Parallel Processing Power of GPU for High Speed Frequent Pattern Mining

D.William Albert, Dr.K.Fayaz, D.Veerabhadra Babu

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Tags: ATI, ATI Radeon HD 5850, Computer science, Data mining, Databases, Java, Machine learning, OpenCL

August 23, 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

Random Forests of Very Fast Decision Trees on GPU for Mining Evolving Big Data Streams

Diego Marron, Albert Bifet, Gianmarco De Francisci Morales

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

July 6, 2014 by hgpu

Increasing Deep Neural Network Acoustic Model Size for Large Vocabulary Continuous Speech Recognition

Andrew L. Maas, Awni Y. Hannun, Christopher T. Lengerich, Peng Qi, Daniel Jurafsky, Andrew Y. Ng

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Tags: Computer science, Machine learning, Neural and Evolutionary Computing, Neural networks, Speech recognition

July 1, 2014 by hgpu

Feature Generation for Quantification of Visual Similarity

Tianning Steven Han

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Tags: Algorithms, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 480, Tesla K20, Thesis

June 23, 2014 by hgpu

MIC-SVM: Designing A Highly Efficient Support Vector Machine For Advanced Modern Multi-Core and Many-Core Architectures

Yang You, Shuaiwen Leon Song, Haohuan Fu, Andres Marquez, Guangwen Yang, Kevin Barker, Kirk W. Cameron, Maryam Mehri Dehnavi, Amanda Peters Randles

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Tags: Computer science, CUDA, Intel Xeon Phi, Machine learning, nVidia, Tesla K20, Vector Machine

June 20, 2014 by hgpu

GPU Implementation of Gaussian Processes

Ying Deng, Edward Khon, Yuanruo Liang, Terence Lim, Jun Wei Ng, Lixiaonan Yin

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 570

June 11, 2014 by hgpu

Mapping parallel programs to heterogeneous multi-core systems

Dominik Grewe

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Source codes

Tags: Algorithms, ATI, ATI Radeon HD 7990, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Thesis

June 5, 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

High-accuracy Optimization by Parallel Iterative Discrete Approximation and GPU Cluster Computing

Machine learning for ultrafast X-ray diffraction patterns on large-scale GPU clusters

A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing

HSApriori: High Speed Association Rule Mining using Apriori Based Algorithm for GPU

Exploiting Parallel Processing Power of GPU for High Speed Frequent Pattern Mining

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

Random Forests of Very Fast Decision Trees on GPU for Mining Evolving Big Data Streams

Increasing Deep Neural Network Acoustic Model Size for Large Vocabulary Continuous Speech Recognition

Feature Generation for Quantification of Visual Similarity

MIC-SVM: Designing A Highly Efficient Support Vector Machine For Advanced Modern Multi-Core and Many-Core Architectures

GPU Implementation of Gaussian Processes

Mapping parallel programs to heterogeneous multi-core systems

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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