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Large-Scale Stochastic Learning using GPUs

Thomas Parnell, Celestine Dunner, Kubilay Atasu, Manolis Sifalakis, Haris Pozidis

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan X, nVidia Quadro M 4000

February 26, 2017 by hgpu

First Experiences Optimizing Smith-Waterman on Intel’s Knights Landing Processor

Enzo Rucci, Carlos Garcia, Guillermo Botella, Armando De Giusti, Marcelo Naiouf, Manuel Prieto-Matias

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Tags: Bioinformatics, Biology, Computer science, Intel Xeon Phi, Sequence alignment, Smith-Waterman algorithm

February 26, 2017 by hgpu

Dynamic Buffer Overflow Detection for GPGPUs

Christopher Erb, Mike Collins, Joseph L. Greathouse

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Tags: AMD FirePro W9100, ATI, Benchmarking, Computer science, OpenCL, Package, Security

February 22, 2017 by hgpu

A 7.663-TOPS 8.2-W Energy-efficient FPGA Accelerator for Binary Convolutional Neural Networks

Yixing Li, Zichuan Liu, Kai Xu, Hao Yu, Fengbo Ren

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Tags: CNN, Computer science, CUDA, Deep learning, Energy-efficient computing, FPGA, Hardware Architecture, Neural networks, nVidia, nVidia GeForce GTX Titan X, Performance

February 22, 2017 by hgpu

MCBooster: a library for fast Monte Carlo generation of phase-space decays on massively parallel platforms

A. A. Alves Jr, M. D. Sokoloff

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Tags: Computational Physics, CUDA, High Energy Physics - Experiment, High Energy Physics - Phenomenology, Intel Xeon Phi, Monte Carlo simulation, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan Z, nVidia Quadro K 2200, OpenMP, Package, Physics, Tesla K40

February 22, 2017 by hgpu

Efficient Large-scale Approximate Nearest Neighbor Search on the GPU

Patrick Wieschollek, Oliver Wang, Alexander Sorkine-Hornung, Hendrik P.A. Lensch

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Tags: Computer science, Computer vision, CUDA, Nearest neighbour, nVidia, nVidia GeForce GTX Titan X, Vector quantization

February 22, 2017 by hgpu

Blocking Self-avoiding Walks Stops Cyber-epidemics: A Scalable GPU-based Approach

Hung T. Nguyen, Alberto Cano, Tam Vu, Thang N. Dinh

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Tags: Algorithms, Computer science, CUDA, Network communications, nVidia, nVidia GeForce GTX Titan X

February 22, 2017 by hgpu

A Survey of Soft-Error Mitigation Techniques for Non-Volatile Memories

Sparsh Mittal

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Tags: classification, Memory, Reliability, Review

February 19, 2017 by sparsh0mittal

Profiling High Level Heterogeneous Programs: Using the SPOC GPGPU framework for OCaml

Mathias Bourgoin, Emmanuel Chailloux, Anastasios Doumoulakis

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Package, Performance

February 18, 2017 by hgpu

LAMMPS’ PPPM Long-Range Solver for the Second Generation Xeon Phi

William McDoniel, Markus Hohnerbach, Rodrigo Canales, Ahmed E. Ismail, Paolo Bientinesi

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Tags: Chemistry, Computer science, Intel Xeon Phi, Molecular dynamics, Performance

February 18, 2017 by hgpu

An Efficient Parallel Data Clustering Algorithm Using Isoperimetric Number of Trees

Ramin Javadi, Saleh Ashkboos

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 850 M

February 18, 2017 by hgpu

Trie Compression for GPU Accelerated Multi-Pattern Matching

Xavier Bellekens, Amar Seeam, Christos Tachtatzis, Robert Atkinson

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Tags: Algorithms, Compression, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 1080

February 18, 2017 by hgpu

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

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

Probe-and-Refine Tuning of Repository Guidance for Coding Agents

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high performance computing on graphics processing units: hgpu.org

Applications

Large-Scale Stochastic Learning using GPUs

First Experiences Optimizing Smith-Waterman on Intel’s Knights Landing Processor

Dynamic Buffer Overflow Detection for GPGPUs

A 7.663-TOPS 8.2-W Energy-efficient FPGA Accelerator for Binary Convolutional Neural Networks

MCBooster: a library for fast Monte Carlo generation of phase-space decays on massively parallel platforms

Efficient Large-scale Approximate Nearest Neighbor Search on the GPU

Blocking Self-avoiding Walks Stops Cyber-epidemics: A Scalable GPU-based Approach

A Survey of Soft-Error Mitigation Techniques for Non-Volatile Memories

Profiling High Level Heterogeneous Programs: Using the SPOC GPGPU framework for OCaml

LAMMPS’ PPPM Long-Range Solver for the Second Generation Xeon Phi

An Efficient Parallel Data Clustering Algorithm Using Isoperimetric Number of Trees

Trie Compression for GPU Accelerated Multi-Pattern Matching

Recent source codes

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

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

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