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OpenCL Task Partitioning in the Presence of GPU Contention

Dominik Grewe, Zheng Wang, and Michael F.P. O'Boyle

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Tags: Computer science, Heterogeneous systems, Intel, Intel HD Graphics 4000, Machine learning, OpenCL, Task scheduling

September 25, 2013 by hgpu

Fast k-NNG construction with GPU-based quick multi-select

Ivan Komarov, Ali Dashti, Roshan D'Souza

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

September 25, 2013 by hgpu

Fast Detection of Overlapping Communities via Online Tensor Methods on GPUs

Furong Huang, Niranjan U N, Mohammad Umar Hakeem, Prateek Verma, Animashree Anandkumar

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Tags: Computer science, CUDA, CULA, Machine learning, nVidia, nVidia Quadro K4000, nVidia Quadro K5000

September 9, 2013 by hgpu

Accelerating Random Forests on CPUs and GPUs for Object-Class Image Segmentation

Benedikt Waldvogel

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Source codes

Tags: Computer science, Computer vision, CUDA, Machine learning, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, Package, Tesla K20, Thesis

August 16, 2013 by hgpu

Deep learning with COTS HPC systems

Adam Coates, Brody Huval, Tao Wang, David J. Wu, Andrew Y. Ng, Bryan Catanzaro

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Tags: Computer science, CUDA, Machine learning, MPI, Neural networks, nVidia, nVidia GeForce GTX 680

June 19, 2013 by hgpu

An Automatic Input-Sensitive Approach for Heterogeneous Task Partitioning

Klaus Kofler, Ivan Grasso, Biagio Cosenza, Thomas Fahringer

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Tags: ATI, ATI Radeon HD 5870, Code generation, Compilers, Computer science, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Task scheduling

April 21, 2013 by hgpu

GPU implementation of a deep learning network for image recognition tasks

Sean Patrick Parker

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Tags: Computer science, Computer vision, CUDA, Image recognition, Machine learning, nVidia, Thesis

March 12, 2013 by hgpu

Utilizing Graphics Processing Units for Network Anomaly Detection

Jonathan D. Hersack

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Tags: Algorithms, Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 280, Security, Thesis

February 27, 2013 by hgpu

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Shuaiwen Song, Chunyi Su, Barry Rountree, Kirk W. Cameron

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Tags: Biomolecules, Computer science, CUDA, Electrostatics, Energy-efficient computing, GPU cluster, Heterogeneous systems, Machine learning, nVidia, Tesla C2075, Tesla M2090

February 18, 2013 by hgpu

Regularization and nonlinearities for neural language models: when are they needed?

Marius Pachitariu, Maneesh Sahani

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Tags: CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 680, Statistics

January 25, 2013 by hgpu

Portable Mapping of Data Parallel Programs to OpenCL for Heterogeneous Systems

Dominik Grewe, Zheng Wang, Michael F.P. O'Boyle

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

January 8, 2013 by hgpu

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

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

NVIDIA Object Oriented Agents

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

See all packages

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high performance computing on graphics processing units: hgpu.org

OpenCL Task Partitioning in the Presence of GPU Contention

Fast k-NNG construction with GPU-based quick multi-select

Fast Detection of Overlapping Communities via Online Tensor Methods on GPUs

Accelerating Random Forests on CPUs and GPUs for Object-Class Image Segmentation

Deep learning with COTS HPC systems

An Automatic Input-Sensitive Approach for Heterogeneous Task Partitioning

GPU implementation of a deep learning network for image recognition tasks

Utilizing Graphics Processing Units for Network Anomaly Detection

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Regularization and nonlinearities for neural language models: when are they needed?

Portable Mapping of Data Parallel Programs to OpenCL for Heterogeneous Systems

Efficient Weighted Histogramming on GPUs with CUDA

Recent source codes

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

NVIDIA Object Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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