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Modelling sea water intrusion in coastal aquifers using heterogeneous computing

Benjamin Donald Cumming

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Tags: CUDA, Earth and Space Sciences, Finite volume method, Heterogeneous systems, nVidia, Tesla C2050, Thesis

July 10, 2013 by hgpu

Hybrid Scheduling for Event-driven Simulation over Heterogeneous Computers

Bilel Ben Romdhanne, Mohamed Said Mosli, Navid Nikaein, Christian Bonnet

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, Task scheduling

July 9, 2013 by hgpu

Comparative study of parallel programming models for multicore computing

Akhtar Ali

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Tags: Benchmarking, Computer science, DSP, Heterogeneous systems, nVidia, OpenCL, OpenMP, Tesla M2050, Thesis

July 7, 2013 by hgpu

Preliminary Experiences with the Uintah Framework on Intel Xeon Phi and Stampede

Qingyu Meng, Alan Humphrey, John Schmidt, Martin Berzins

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Tags: Computer science, Heterogeneous systems, Intel, Intel Phi, Performance

July 2, 2013 by hgpu

Generating Efficient Data Movement Code for Heterogeneous Architectures with Distributed-Memory

Roshan Dathathri, Chandan Reddy, Thejas Ramashekar, Uday Bondhugula

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Tags: ATI, ATI FirePro V4800, ATI Radeon HD 6550, Code generation, Computer science, Heterogeneous systems, nVidia, Tesla C2050

July 1, 2013 by hgpu

Exploiting multi-level parallelism in streaming applications for heterogeneous platforms with GPUs

Ana Balevic

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Tags: Code generation, Compilers, Computer science, CUDA, Data parallelism, Heterogeneous systems, nVidia, Tesla C2050, Thesis

July 1, 2013 by hgpu

HadoopCL: MapReduce on Distributed Heterogeneous Platforms Through Seamless Integration of Hadoop and OpenCL

Max Grossman, Mauricio Breternitz, Vivek Sarkar

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Tags: APU, ATI, Computer science, Heterogeneous systems, Java, MapReduce, nVidia, OpenCL, Tesla M2050

June 30, 2013 by hgpu

A model of dynamic compilation for heterogeneous compute platforms

Andrew Kerr

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, OpenCL, PTX, Thesis

June 29, 2013 by hgpu

Delaunay Triangulation in R3 on the GPU

Ashwin Nanjappa

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Source codes

Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, Package, Thesis, Voronoi diagram

June 18, 2013 by hgpu

Accelerating GPU Programs by Reducing Irregular Control Flow and Memory Access

Tomohiro Okuyama

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Tags: Algorithms, Biophysics, CUDA, Differential equations, Heterogeneous systems, nVidia, ODEs, Ordinary differential equations, Physics, Tesla C2070, Thesis

June 18, 2013 by hgpu

Auto-Tunning of Data Communication on Heterogeneous Systems

Marc Jorda, Ivan Tanasic, Javier Cabezas, Lluis Vilanova, Isaac Gelado, Nacho Navarro

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla C2050, Tesla C2070, Tesla M2090

June 17, 2013 by hgpu

An Analysis of Conventional and Heterogeneous Workloads on Production Supercomputing Resources

Jonathan Allen Berkhahn

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Tags: Cloud, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla M2050, Tesla S2050

June 13, 2013 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

Modelling sea water intrusion in coastal aquifers using heterogeneous computing

Hybrid Scheduling for Event-driven Simulation over Heterogeneous Computers

Comparative study of parallel programming models for multicore computing

Preliminary Experiences with the Uintah Framework on Intel Xeon Phi and Stampede

Generating Efficient Data Movement Code for Heterogeneous Architectures with Distributed-Memory

Exploiting multi-level parallelism in streaming applications for heterogeneous platforms with GPUs

HadoopCL: MapReduce on Distributed Heterogeneous Platforms Through Seamless Integration of Hadoop and OpenCL

A model of dynamic compilation for heterogeneous compute platforms

Delaunay Triangulation in R3 on the GPU

Accelerating GPU Programs by Reducing Irregular Control Flow and Memory Access

Auto-Tunning of Data Communication on Heterogeneous Systems

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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