high performance computing on graphics processing units: hgpu.org

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Out-of-core Implementation for Accelerator Kernels on Heterogeneous Clouds

Hamidreza Khaleghzadeh, Ziming Zhong, Ravi Reddy, Alexey Lastovetsky

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Tags: BLAS, Cloud, Computer science, CUBLAS, CUDA, FPGA, Heterogeneous systems, Intel Xeon Phi, Matrix multiplication, nVidia, OpenCL, Package, Virtualization

September 16, 2017 by hgpu

Monte Carlo methods for massively parallel computers

Martin Weigel

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Tags: CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX Titan X, Phase transition, Physics, Spin Systems, Tesla C1060, Tesla K20

September 16, 2017 by hgpu

Meta Networks for Neural Style Transfer

Falong Shen, Shuicheng Yan, Gang Zeng

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Tags: Caffe, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX Titan X, Package

September 16, 2017 by hgpu

Empower Sequence Labeling with Task-Aware Neural Language Model

Liyuan Liu, Jingbo Shang, Frank Xu, Xiang Ren, Huan Gui, Jian Peng, Jiawei Han

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Tags: Computer science, Machine learning, Neural networks, NLP, nVidia, nVidia GeForce GTX 1080, Package, Python, Torch

September 16, 2017 by hgpu

GPU-Accelerated Parallel Finite-Difference Time-Domain Method for Electromagnetic Waves Propagation in Unmagnetized Plasma Media

Xi-min Wang, Lang-lang Xiong, Song Liu, Zhi-yun Peng, Shuang-ying Zhong

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Tags: Computational Physics, CUDA, FDTD, Finite-difference time-domain, nVidia, nVidia GeForce GT 650 M, Physics, Plasma physics

September 12, 2017 by hgpu

Sorting with GPUs: A Survey

Dmitri I. Arkhipov, Di Wu, Keqin Li, Amelia C. Regan

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Tags: Algorithms, Computer science, CUDA, nVidia, Sorting, survey

September 12, 2017 by hgpu

Report: Performance comparison between C2075 and P100 GPU cards using cosmological correlation functions

Miguel Cardenas-Montes, Ivan Mendez-Jimenez, Juan Jose Rodriguez-Vazquez, Jose Maria Hernandez Calama

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Tags: Computer science, CUDA, nVidia, Performance, Tesla C2075, Tesla P100

September 12, 2017 by hgpu

A Comparative Study of 2D Numerical Methods with GPU Computing

Ben J. Zimmerman, Jonathan D. Regele, Bong Wie

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Tags: Computer science, CUDA, Finite volume method, Numerical simulation, nVidia, Tesla K20

September 12, 2017 by hgpu

Beyond 16GB: Out-of-Core Stencil Computations

Istvan Z. Reguly, Gihan R. Mudalige, Michael B. Giles

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Tags: Computer science, CUDA, Intel Xeon Phi, MPI, nVidia, Stencil computation, Tesla P100

September 9, 2017 by hgpu

Progressive Clustering of Big Data with GPU Acceleration and Visualization

Jun Wang, Eric Papenhausen, Bing Wang, Sungsoo Ha, Alla Zelenyuk, Klaus Mueller

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Tags: Algorithms, big data, Clustering, Computer science, CUDA, nVidia, Tesla K20, Visualization

September 9, 2017 by hgpu

Data Layout Oriented Compilation Techniques in Vectorization for Multi-/Many-cores

Shixiong Xu

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 645, nVidia Jetson TK1

September 9, 2017 by hgpu

Generating Custom Code for Efficient Query Execution on Heterogeneous Processors

Sebastian Bress, Bastian Kocher, Henning Funke, Tilmann Rabl, Volker Markl

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Tags: APU, Computer science, Databases, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Tesla K40

September 7, 2017 by hgpu

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

nvsass-disassembler

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

MaxKernel: Intelligent TPU Kernel Engineering Agents

MaxKernel: Agentic Kernel Generation for TPUs

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

Hardware-Aware FP4 FlashAttention-4

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high performance computing on graphics processing units: hgpu.org

Monte Carlo methods for massively parallel computers

Meta Networks for Neural Style Transfer

Empower Sequence Labeling with Task-Aware Neural Language Model

GPU-Accelerated Parallel Finite-Difference Time-Domain Method for Electromagnetic Waves Propagation in Unmagnetized Plasma Media

Sorting with GPUs: A Survey

Report: Performance comparison between C2075 and P100 GPU cards using cosmological correlation functions

A Comparative Study of 2D Numerical Methods with GPU Computing

Beyond 16GB: Out-of-Core Stencil Computations

Progressive Clustering of Big Data with GPU Acceleration and Visualization

Data Layout Oriented Compilation Techniques in Vectorization for Multi-/Many-cores

Generating Custom Code for Efficient Query Execution on Heterogeneous Processors

Recent source codes

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

nvsass-disassembler

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

MaxKernel: Intelligent TPU Kernel Engineering Agents

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

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