high performance computing on graphics processing units: hgpu.org

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Accelerating Web Search using GPUs

Rimon Tadros

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Tags: C++ AMP, Computer science, nVidia, nVidia GeForce GTX 660 Ti, nVidia GeForce GTX 750 Ti, Search, Thesis

September 8, 2015 by hgpu

Accelerating Multiple Compound Comparison Using LINGO-based Load-Balancing Strategies on Multi-GPUs

Chun-Yuan Lin, Chung-Hung Wang, Che-Lun Hung, Yu-Shiang Lin

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Tags: Computer science, CUDA, load balancing, nVidia, OpenMP, Tesla K20

September 8, 2015 by hgpu

Assessing the hardness of SVP algorithms in the presence of CPUs and GPUs

Fabio Jose Goncalves Correia

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Tags: Algorithms, Computer science, CUDA, MPI, nVidia, Quantum computing, Security, Thesis, Voronoi diagram

September 8, 2015 by hgpu

Contributions to the Efficient Use of General Purpose Coprocessors: Kernel Density Estimation as Case Study

Unai Lopez Novoa

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Tags: Algorithms, ATI, ATI Radeon HD 6950, Computational Complexity, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 650, OpenCL, Thesis

September 8, 2015 by hgpu

Waste Not, Want Not! Managing relational data in asymmetric memories

Holger Pirk

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Tags: ATI, ATI Radeon HD 5850, Computer science, Databases, nVidia, nVidia GeForce GTX 480, OpenCL, Thesis

September 5, 2015 by hgpu

Virtualizing Data Parallel Systems for Portability, Productivity, and Performance

Janghaeng Lee

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Tags: Computer science, LLVM, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX 760, OpenCL, Thesis, Virtualization

September 5, 2015 by hgpu

Parallel Execution of the ASP Computation – an Investigation on GPUs

Agostino Dovier, Andrea Formisano, Enrico Pontelli, Flavio Vella

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, nVidia GeForce GT 520, nVidia GeForce GT 640, nVidia GeForce GTX Titan X, Search strategies, Tesla C2075, Tesla K20, Tesla K80

September 5, 2015 by hgpu

Convolutional Neural Network for Sentence Classification

Yahui Chen

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Tags: CNN, Computer science, CUDA, Deep learning, Machine learning, Neural networks, NLP, nVidia, nVidia GeForce GTX Titan X, Thesis

September 5, 2015 by hgpu

A Comparison of High-Level Design Tools for SoC-FPGA on Disparity Map Calculation Example

Shaodong Qin, Mladen Berekovic

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Tags: ARM, Computer science, FPGA, OpenCL

September 3, 2015 by hgpu

OpenCL 2.0 for FPGAs using OCLAcc

Franz Richter-Gottfried, Alexander Ditter, Dietmar Fey

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Tags: ARM, Computer science, FPGA, OpenCL

September 3, 2015 by hgpu

Exploiting Hyper-Loop Parallelism in Vectorization to Improve Memory Performance on CUDA GPGPU

Shixiong Xu, David Gregg

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Tags: ARM, Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 645, nVidia Jetson TK1

September 3, 2015 by hgpu

An Asynchronous Event Communication Technique for Soft Real-Time GPGPU Applications

Alexander Vestman

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Tags: Computer science, nVidia, nVidia GeForce GTX 760, OpenGL, Thesis

August 31, 2015 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

Accelerating Web Search using GPUs

Accelerating Multiple Compound Comparison Using LINGO-based Load-Balancing Strategies on Multi-GPUs

Assessing the hardness of SVP algorithms in the presence of CPUs and GPUs

Contributions to the Efficient Use of General Purpose Coprocessors: Kernel Density Estimation as Case Study

Waste Not, Want Not! Managing relational data in asymmetric memories

Virtualizing Data Parallel Systems for Portability, Productivity, and Performance

Parallel Execution of the ASP Computation – an Investigation on GPUs

Convolutional Neural Network for Sentence Classification

A Comparison of High-Level Design Tools for SoC-FPGA on Disparity Map Calculation Example

OpenCL 2.0 for FPGAs using OCLAcc

Exploiting Hyper-Loop Parallelism in Vectorization to Improve Memory Performance on CUDA GPGPU

An Asynchronous Event Communication Technique for Soft Real-Time GPGPU Applications

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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