high performance computing on graphics processing units: hgpu.org

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Acceleration of Linear Finite-Difference Poisson-Boltzmann Methods on Graphics Processing Units

Ruxi Qi, Wesley M. Botello-Smith, Ray Luo

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Tags: Biomolecules, Biophysics, Boltzmann equation, Computational Physics, CUBLAS, CUDA, Electrostatics, Molecular simulation, nVidia, nVidia GeForce GTX 980 Ti, Physics, Poisson Boltzmann

April 11, 2017 by hgpu

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

Maria Barreda Vaya

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Intel Xeon Phi, Linear Algebra, MPI, nVidia, OmpSs, Tesla C2050, Thesis

April 11, 2017 by hgpu

A modular GPU raytracer using OpenCL for non-interactive graphics

Henrique Nunes Jung, Vinicius Jurinic Cassol

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 970, OpenCL, Package, Raytracing, Rendering

April 11, 2017 by hgpu

Vectorization of Hybrid Breadth First Search on the Intel Xeon Phi

Mireya Paredes, Graham Riley, Mikel Lujan

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Tags: Algorithms, Computer science, Intel Xeon Phi, OpenMP, Parallelization

April 11, 2017 by hgpu

Design Exploration of AES Accelerators on FPGAs and GPUs

Vincenzo Conti, Salvatore Vitabile

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Tags: AES, Computer science, FPGA, nVidia, nVidia GeForce GT 520, nVidia GeForce GT 555 M, OpenCL, Security

April 7, 2017 by hgpu

Load Balancing for Constraint Solving with GPUs

Pedro Roque, Vasco Pedro, Salvador Abreu

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Tags: ATI, ATI Radeon HD 7990, Computer science, Heterogeneous systems, Intel Xeon Phi, load balancing, nVidia, nVidia GeForce GTX 980 M, OpenCL, Tesla K20

April 7, 2017 by hgpu

Cascaded Segmentation-Detection Networks for Word-Level Text Spotting

Siyang Qin, Roberto Manduchi

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Tags: Algorithms, Caffe, Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX Titan X

April 7, 2017 by hgpu

Optimizing Communication by Compression for Multi-GPU Scalable Breadth-First Searches

Julian Romera

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenMPI, Performance, Tesla K80, Tesla M2090, Thesis

April 7, 2017 by hgpu

Merge or Separate? Multi-job Scheduling for OpenCL Kernels on CPU/GPU Platforms

Yuan Wen, Michael F.P. O'Boyle

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Tags: AMD Radeon HD 7970, ATI, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 780, OpenCL

April 3, 2017 by hgpu

Evaluation of Libraries for Parallel Computing in Haskell – A Case Study with a Super-resolution Application

Takuya Matsumoto, Kiminori Matsuzaki

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Tags: Computer science, CUDA, Haskell, Image processing, MRI, nVidia, nVidia GeForce GTX 750 Ti

April 3, 2017 by hgpu

Sparse Matrix-Vector Multiplication on GPGPUs

Salvatore Filippone, Valeria Cardellini, Davide Barbieri, Alessandro Fanfarillo

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Tags: Computer science, CUDA, Fortran, nVidia, nVidia GeForce GTX 660, Package, Review, Sparse matrix, Tesla K20, Tesla K40, Tesla M2070

April 3, 2017 by hgpu

Chai: Collaborative Heterogeneous Applications for Integrated-architectures

Juan Gomez-Luna, Izzat El Hajj, Li-Wen Chang, Victor Garcia-Flores, Simon Garcia de Gonzalo, Thomas B. Jablin, Antonio J. Pena, Wen-mei Hwu

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL

April 3, 2017 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

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

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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high performance computing on graphics processing units: hgpu.org

Programming

Acceleration of Linear Finite-Difference Poisson-Boltzmann Methods on Graphics Processing Units

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

A modular GPU raytracer using OpenCL for non-interactive graphics

Vectorization of Hybrid Breadth First Search on the Intel Xeon Phi

Design Exploration of AES Accelerators on FPGAs and GPUs

Load Balancing for Constraint Solving with GPUs

Cascaded Segmentation-Detection Networks for Word-Level Text Spotting

Optimizing Communication by Compression for Multi-GPU Scalable Breadth-First Searches

Merge or Separate? Multi-job Scheduling for OpenCL Kernels on CPU/GPU Platforms

Evaluation of Libraries for Parallel Computing in Haskell – A Case Study with a Super-resolution Application

Sparse Matrix-Vector Multiplication on GPGPUs

Chai: Collaborative Heterogeneous Applications for Integrated-architectures

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

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

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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