high performance computing on graphics processing units: hgpu.org

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Data Analysis of Minimally-Structured Heterogeneous Logs: An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes

Chang Liu

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Tags: Computer science, CUDA, Deep learning, LSTM, NLP, nVidia, Package, RNN, Thesis

September 13, 2016 by hgpu

An efficient numerical method for solving the Boltzmann equation in multidimensions

Giacomo Dimarco, Raphael Loubere, Jacek Narski, Thomas Rey

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Tags: Algorithms, Boltzmann equation, cfd, CUDA, Fluid dynamics, Mathematics, MPI, Numerical Analysis, nVidia, OpenMP, Physics

September 13, 2016 by hgpu

OpenMP as a High-Level Specification Language for Parallelism And its use in Evaluating Parallel Programming Systems

Max Grossman, Jun Shirako, Vivek Sarkar

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Tags: Code generation, Compilers, Computer science, CUDA, LLVM, nVidia, OpenMP, Package

September 13, 2016 by hgpu

Scheduling of Linear Algebra Kernels on Multiple Heterogeneous Resources

Olivier Beaumont, Terry Cojean, Lionel Eyraud-Dubois, Abdou Guermouche, Suraj Kumar

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Tesla K40

September 13, 2016 by hgpu

A New Architecture for Optimization Modeling Frameworks

Matt Wytock, Steven Diamond, Felix Heide, Stephen Boyd

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Tags: Algorithms, CUDA, Deep learning, Linear Algebra, Mathematics, nVidia, nVidia GeForce GTX Titan X, Package, Python

September 13, 2016 by hgpu

An Implementation of Real-Time Phased Array Radar Fundamental Functions on a DSP-Focused, High-Performance, Embedded Computing Platform

Xining Yu, Yan Zhang, Ankit Patel, Allen Zahrai, Mark Weber

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Tags: DSP, Filtering, OpenCL, OpenMP, Signal processing

September 10, 2016 by hgpu

GPU-ArraySort: A parallel, in-place algorithm for sorting large number of arrays

Muaaz Awan, Fahad Saeed

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Tags: Algorithms, big data, Computer science, CUDA, nVidia, Package, Sorting, Tesla K40

September 10, 2016 by hgpu

System Design Principles for Heterogeneous Resource Management and Scheduling in Accelerator-Based Systems

Dipanjan Sengupta

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Tags: Algorithms, Cloud, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro 2000, nVidia Quadro 4000, Task scheduling, Tesla C2050, Tesla C2070, Tesla K20, Thesis

September 10, 2016 by hgpu

3D Object Recognition with Convolutional Neural Networks

Alberto Garcia-Garcia

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Tags: CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GT 730, nVidia GeForce GTX Titan X, Tesla K40, Thesis

September 10, 2016 by hgpu

OpenSBLI: A framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures

Christian T. Jacobs, Satya P. Jammy, Neil D. Sandham

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Tags: cfd, Code generation, Computer science, CUDA, Finite difference, Fluid dynamics, Mathematical Software, MPI, nVidia, OpenCL, Tesla K40

September 10, 2016 by hgpu

Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks

Chen Zhang, Zhenman Fang, Peipei Zhou, Peichen Pan, Jason Cong

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Tags: Caffe, Computer science, CUDA, Deep learning, DSP, FPGA, Neural networks, nVidia, Tesla K40

September 8, 2016 by hgpu

A Lightweight Approach to Performance Portability with targetDP

Alan Gray, Kevin Stratford

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Tags: Computer science, CUDA, Intel Xeon Phi, nVidia, Package, Performance, performance portability, QCD, Tesla K20, Tesla K40

September 8, 2016 by hgpu

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Data Analysis of Minimally-Structured Heterogeneous Logs: An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes

An efficient numerical method for solving the Boltzmann equation in multidimensions

OpenMP as a High-Level Specification Language for Parallelism And its use in Evaluating Parallel Programming Systems

Scheduling of Linear Algebra Kernels on Multiple Heterogeneous Resources

A New Architecture for Optimization Modeling Frameworks

An Implementation of Real-Time Phased Array Radar Fundamental Functions on a DSP-Focused, High-Performance, Embedded Computing Platform

GPU-ArraySort: A parallel, in-place algorithm for sorting large number of arrays

3D Object Recognition with Convolutional Neural Networks

OpenSBLI: A framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures

Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks

A Lightweight Approach to Performance Portability with targetDP

Recent source codes

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Device Virtual Machine (DVM)

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

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