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Sequential Code Parallelization for Multi-core Embedded Systems: A Survey of Models, Algorithms and Tools

Jorge Alberto Castro Godinez

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Tags: Computer science, Parallelization, Review, Thesis

October 22, 2015 by hgpu

A linguistic approach to concurrent, distributed, and adaptive programming across heterogeneous platforms

Paul Harvey

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Tags: Computer science, Heterogeneous systems, OpenCL, Thesis

October 22, 2015 by hgpu

Stadium Hashing: Scalable and Flexible Hashing on GPUs

Farzad Khorasani, Mehmet E. Belviranli, Rajiv Gupta, Laxmi N. Bhuyan

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 780

October 22, 2015 by hgpu

Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

Lev E. Givon, Aurel A. Lazar

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Tags: Biology, Computer science, CUDA, nVidia, OpenMPI, Tesla K20

October 22, 2015 by hgpu

Self-Adapting Parallel Framework for Long-Term Object Tracking

Salim Mohammed Ali

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Tags: AMD Radeon HD 8970 M, ATI, Computer science, Computer vision, nVidia, nVidia GeForce GTX 580, OpenCL, Thesis

October 18, 2015 by hgpu

A Network Intrusion Detection System Framework based on Hadoop and GPGPU

Sanraj Bandre, Jyoti Nandimath

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Tags: Computer science, CUDA, Hadoop, nVidia, Security, Tesla K20

October 18, 2015 by hgpu

MetaFork: A Compilation Framework for Concurrency Models Targeting Hardware Accelerators and Its Application to the Generation of Parametric CUDA Kernels

Changbo Chen, Xiaohui Chen, Abdoul-Kader Keita, Marc Moreno Maza, Ning Xie

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Tags: Code generation, Computer science, CUDA, nVidia, Package

October 18, 2015 by hgpu

Comparison of Thread Execution Methods for GPU-oriented OpenCL Programs on Multicore Processors

Naohisa Hojo, Ittetsu Taniguchi, Hiroyuki Tomiyama

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Tags: Benchmarking, Computer science, OpenCL, Performance

October 16, 2015 by hgpu

Accelerating Applications with Pattern-specific Optimizations on Accelerators and Coprocessors

Linchuan Chen

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Tags: Computer science, CUDA, Heterogeneous systems, MapReduce, Matrix multiplication, MPI, nVidia, Sparse matrix, Task scheduling, Tesla M2070, Thesis

October 13, 2015 by hgpu

A Hybrid CPU/GPU Pattern-Matching Algorithm for Deep Packet Inspection

Chun-Liang Lee, Yi-Shan Lin, Yaw-Chung Chen

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Tags: Algorithms, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GTX 680, Security

October 13, 2015 by hgpu

Optimal Piecewise Linear Function Approximation for GPU-based Applications

Daniel Berjon, Guillermo Gallego, Carlos Cuevas, Francisco Moran, Narciso Garcia

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Tags: Computer science, Computer vision, CUDA, Numerical Analysis, nVidia, nVidia GeForce GTX 580

October 13, 2015 by hgpu

Fast and Accurate Poisson Denoising with Optimized Nonlinear Diffusion

Wensen Feng, Yunjin Chen

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Tags: CNN, Computer science, Computer vision, Microscopy, nVidia, nVidia GeForce GTX 780 Ti, Signal denoising

October 13, 2015 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

Sequential Code Parallelization for Multi-core Embedded Systems: A Survey of Models, Algorithms and Tools

A linguistic approach to concurrent, distributed, and adaptive programming across heterogeneous platforms

Stadium Hashing: Scalable and Flexible Hashing on GPUs

Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

Self-Adapting Parallel Framework for Long-Term Object Tracking

A Network Intrusion Detection System Framework based on Hadoop and GPGPU

MetaFork: A Compilation Framework for Concurrency Models Targeting Hardware Accelerators and Its Application to the Generation of Parametric CUDA Kernels

Comparison of Thread Execution Methods for GPU-oriented OpenCL Programs on Multicore Processors

Accelerating Applications with Pattern-specific Optimizations on Accelerators and Coprocessors

A Hybrid CPU/GPU Pattern-Matching Algorithm for Deep Packet Inspection

Optimal Piecewise Linear Function Approximation for GPU-based Applications

Fast and Accurate Poisson Denoising with Optimized Nonlinear Diffusion

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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