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HAM – Heterogenous Active Messages for Efficient Offloading on the Intel Xeon Phi

Matthias Noack

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, MPI

June 17, 2014 by hgpu

An in-depth performance analysis of irregular workloads on VLIW APU

Matthew Doerksen

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Tags: APU, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, OpenCL, Performance, Thesis

June 16, 2014 by hgpu

Toward OpenCL Automatic Multi-Device Support

Henry Sylvain, Alexandre Denis, Denis Barthou, Marie-Christine Counilh, Raymond Namyst

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Tags: ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Tesla M2075

June 15, 2014 by hgpu

Dynamic loop vectorization for executing OpenCL kernels on CPUs

Izzat El Hajj

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Tags: Computer science, Heterogeneous systems, OpenCL, Performance, Thesis

June 14, 2014 by hgpu

Unified Development for Mixed Multi-GPU and Multi-Coprocessor Environments using a Lightweight Runtime Environment

Azzam Haidar, Chongxiao Cao, Asim YarKhan, Piotr Luszczek, Stanimire Tomov, Khairul Kabir, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, Linear Algebra, nVidia, Tesla K20, Tesla M2090

June 14, 2014 by hgpu

Secure Distributed Computing on a Manycore Cloud

Flavio Lombardi

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Tags: Cloud, Computer science, CUDA, Data acquisition, Distributed computing, Heterogeneous systems, nVidia, nVidia GeForce GT 640, Security, Tesla C2050, Thesis

June 13, 2014 by hgpu

Multi-threaded Kernel Offloading to GPGPU Using Hyper-Q on Kepler Architecture

Florian Wende, Thomas Steinke, Frank Cordes

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20, Tesla M2090

June 12, 2014 by hgpu

Native Offload of Haskell Repa Programs to GPGPU

H. Liu, L.E. Day, N. Glew, T.A. Anderson, R. Barik

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Tags: Heterogeneous systems, Intel HD 4600, OpenCL, Parallelization, Programming techniques

June 8, 2014 by hgpu

Mapping parallel programs to heterogeneous multi-core systems

Dominik Grewe

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Tags: Algorithms, ATI, ATI Radeon HD 7990, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Thesis

June 5, 2014 by hgpu

Loo.py: transformation-based code generation for GPUs and CPUs

Andreas Klockner

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Source codes

Tags: ATI, ATI Radeon HD 7990, Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL, Package, Programming Languages, PyOpenCL, Python

June 2, 2014 by hgpu

Region Templates: Data Representation and Management for Large-Scale Image Analysis

George Teodoro, Tony Pan, Tahsin Kurc, Jun Kong, Lee Cooper, Scott Klasky, Joel Saltz

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Tags: Computer science, CUDA, Heterogeneous systems, Hybrid computing, Microscopy, nVidia, OpenCV, Tesla M2090

June 2, 2014 by hgpu

A GPU-Based Simulation Kernel within Heterogeneous Collaborative Computation on Large-Scale Artificial Society

Li Zhen, Qiuxiao Gang, Guo Gang, Chen Bin

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Task scheduling, Tesla C2050

May 24, 2014 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

HAM – Heterogenous Active Messages for Efficient Offloading on the Intel Xeon Phi

An in-depth performance analysis of irregular workloads on VLIW APU

Toward OpenCL Automatic Multi-Device Support

Dynamic loop vectorization for executing OpenCL kernels on CPUs

Unified Development for Mixed Multi-GPU and Multi-Coprocessor Environments using a Lightweight Runtime Environment

Multi-threaded Kernel Offloading to GPGPU Using Hyper-Q on Kepler Architecture

Native Offload of Haskell Repa Programs to GPGPU

Mapping parallel programs to heterogeneous multi-core systems

Loo.py: transformation-based code generation for GPUs and CPUs

Region Templates: Data Representation and Management for Large-Scale Image Analysis

A GPU-Based Simulation Kernel within Heterogeneous Collaborative Computation on Large-Scale Artificial Society

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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