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A Parallelizing Matlab Compiler Framework and Run time for Heterogeneous Systems

Sam Skalicky, Sonia Lopez, Marcin Lukowiak, Andrew G. Schmidt

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Tags: Code generation, Computer science, FPGA, Heterogeneous systems, Matlab

August 21, 2015 by hgpu

Implementing Computer Vision Functions with OpenCL on the Qualcomm Adreno 420

Staff of Berkeley Design Technology

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Tags: Algorithms, ARM, Computer science, Computer vision, OpenCL

August 21, 2015 by hgpu

GPU computing with OpenCL to model 2D elastic wave propagation: exploring memory usage

Ursula Iturraran-Viveros, Miguel Molero-Armenta

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Tags: Condensed matter, Instrumentation and measurement, nVidia, OpenCL, Package, Physics, PyOpenCL, Python

August 21, 2015 by hgpu

OpenCL-Based Design of an FPGA Accelerator for Phase-Based Correspondence Matching

Shunsuke Tatsumi, Masanori Hariyama, Mamoru Miura, Koichi Ito, Takafumi Aoki

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Tags: Computer science, FPGA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Stereo vision

August 18, 2015 by hgpu

Parallelizing a high-order WENO scheme for complicated flow structures on GPU and MIC

Liang Deng, Fang Wang, Han-Li Bai, Qing-Xin Xu

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Tags: CUDA, Fluid dynamics, Intel Xeon Phi, nVidia, Tesla K20, Tesla M2050

August 18, 2015 by hgpu

Runtime Code Generation and Data Management for Heterogeneous Computing in Java

Juan Jose Fumero, Toomas Remmelg, Michel Steuwer, Christophe Dubach

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Tags: AMD Radeon R9 295X2, ATI, Code generation, Computer science, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX Titan, OpenCL

August 18, 2015 by hgpu

RubiCL, a Library Providing Automatic Parallelisation on CPU and GPU devices

Aaron Cronin

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Tags: Computer science, nVidia, nVidia GeForce GTX 670, OpenCL, Ruby

August 18, 2015 by hgpu

Optimizing OpenCL Local Work Group Size With Machine Learning

Markus Schlafli

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Tags: ATI, ATI Radeon HD 7850, Computer science, Machine learning, OpenCL, Performance, PTX

August 18, 2015 by hgpu

A Tool for Automatically Suggesting Source-Code Optimizations for Complex GPU Kernels

Saeed Taheri, Apan Qasem, Martin Burtscher

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, Performance, Tesla K20

August 14, 2015 by hgpu

MPC: A Massively Parallel Compression Algorithm for Scientific Data

Annie Yang, Hari Mukka, Farbod Hesaaraki, Martin Burtscher

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, Tesla K40

August 14, 2015 by hgpu

Bufferless NOC Simulation of Large Multicore System on GPU Hardware

Navin Kumar, Aryabartta Sahu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 690

August 14, 2015 by hgpu

Automatic classification of object code using machine learning

John Clemens

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Tags: Computer science, CUDA, Machine learning, nVidia, Security

August 14, 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

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

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

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

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

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high performance computing on graphics processing units: hgpu.org

Applications

A Parallelizing Matlab Compiler Framework and Run time for Heterogeneous Systems

Implementing Computer Vision Functions with OpenCL on the Qualcomm Adreno 420

GPU computing with OpenCL to model 2D elastic wave propagation: exploring memory usage

OpenCL-Based Design of an FPGA Accelerator for Phase-Based Correspondence Matching

Parallelizing a high-order WENO scheme for complicated flow structures on GPU and MIC

Runtime Code Generation and Data Management for Heterogeneous Computing in Java

RubiCL, a Library Providing Automatic Parallelisation on CPU and GPU devices

Optimizing OpenCL Local Work Group Size With Machine Learning

A Tool for Automatically Suggesting Source-Code Optimizations for Complex GPU Kernels

MPC: A Massively Parallel Compression Algorithm for Scientific Data

Bufferless NOC Simulation of Large Multicore System on GPU Hardware

Automatic classification of object code using machine learning

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

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

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

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

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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