high performance computing on graphics processing units: hgpu.org

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Multicore architecture and cache optimization techniques for solving graph problems

Alvaro Tzul

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Tags: Computer science, CUDA, Graph theory, nVidia

July 15, 2018 by hgpu

Data-Parallel Hashing Techniques for GPU Architectures

Brenton Lessley

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Tags: Computer science, CUDA, Hashing, nVidia

July 15, 2018 by hgpu

Energy Consumption of Algorithms for Solving the Compressible Navier-Stokes Equations on CPU’s, GPU’s and KNL’s

Satya P. Jammy, Christian T. Jacobs, David J. Lusher, Neil D. Sandham

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Tags: CUDA, Finite difference, Fluid dynamics, Intel Xeon Phi, Navier-Stokes equations, NSEs, nVidia, Tesla K40

July 7, 2018 by hgpu

FluidFFT: common API (C++ and Python) for Fast Fourier Transform HPC libraries

Ashwin Vishnu Mohanan, Cyrille Bonamy, Pierre Augier

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Tags: Benchmarking, cfd, CUDA, FFT, Fluid dynamics, MPI, Package, Python

July 7, 2018 by hgpu

A Survey on Agent-based Simulation using Hardware Accelerators

Jiajian Xiao, Philipp Andelfinger, David Eckhoff, Wentong Cai, Alois Knoll

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, OpenCL, Overview

July 5, 2018 by hgpu

XGBoost: Scalable GPU Accelerated Learning

Rory Mitchell, Andrey Adinets, Thejaswi Rao, Eibe Frank

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Tags: Computer science, CUDA, Java, Machine learning, nVidia, Package, Python, R, Scala, Tesla V100

July 5, 2018 by hgpu

Analysis-driven Engineering of Comparison-based Sorting Algorithms on GPUs

Ben Karsin, Volker Weichert, Henri Casanova, John Iacono, Nodari Sitchinava

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 770, nVidia Quadro M 4000, Performance, Sorting, Tesla K40

July 1, 2018 by hgpu

Ray-traced Radiative Transfer on Massively Threaded Architectures

Samuel Paul Thomson

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Tags: Astrophysics, CUDA, nVidia, Raytracing, Tesla M2090, Thesis

July 1, 2018 by hgpu

Computing dynamics of thin films via large scale GPU-based simulations

Michael-Angelo Y.-H. Lam, Linda J. Cummings, Lou Kondic

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Tags: cfd, CUDA, Differential equations, Fluid dynamics, Liquid crystals, nVidia, nVidia GeForce GTX Titan X, Partial differential equations, PDEs

June 28, 2018 by hgpu

Research on the simulation of PF-LBM model based on MPI+CUDA mixed granularity parallel

Changsheng Zhu, Jieqiong Liu, Li Feng, Xin Deng

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, Lattice Boltzmann model, MPI, nVidia, Tesla M2090

June 24, 2018 by hgpu

Go game move prediction using convolutional neural network

Marek Korenciak

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Tags: Caffe, CNN, Computer science, CUDA, Deep learning, Games, nVidia, nVidia GeForce GTX 1080 Ti, Package, Thesis

June 24, 2018 by hgpu

Neural Code Comprehension: A Learnable Representation of Code Semantics

Tal Ben-Nun, Alice Shoshana Jakobovits, Torsten Hoefler

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Tags: ATI, ATI Radeon HD 7970, Code generation, Computer science, CUDA, Deep learning, LLVM, LSTM, Machine learning, NLP, nVidia, nVidia GeForce GTX 970, OpenCL, Programming Languages, RNN

June 20, 2018 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

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high performance computing on graphics processing units: hgpu.org

Multicore architecture and cache optimization techniques for solving graph problems

Data-Parallel Hashing Techniques for GPU Architectures

Energy Consumption of Algorithms for Solving the Compressible Navier-Stokes Equations on CPU’s, GPU’s and KNL’s

FluidFFT: common API (C++ and Python) for Fast Fourier Transform HPC libraries

A Survey on Agent-based Simulation using Hardware Accelerators

XGBoost: Scalable GPU Accelerated Learning

Analysis-driven Engineering of Comparison-based Sorting Algorithms on GPUs

Ray-traced Radiative Transfer on Massively Threaded Architectures

Computing dynamics of thin films via large scale GPU-based simulations

Research on the simulation of PF-LBM model based on MPI+CUDA mixed granularity parallel

Go game move prediction using convolutional neural network

Neural Code Comprehension: A Learnable Representation of Code Semantics

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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