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Review of Memory/Cache Management Technologies used on Heterogeneous Computing Systems

Mustafa Ali, Tarik Ozkul

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Tags: Computer science, Heterogeneous systems, Memory, Review

May 23, 2014 by hgpu

An Extensible Component-based Approach to Simulation Systems on Heterogeneous Clusters

Roger Viet Hoang

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 570, Performance, Tesla C2050, Thesis, Virtual reality

May 23, 2014 by hgpu

Petascale Application of a Coupled CPU-GPU Algorithm for Simulation and Analysis of Multiphase Flow Solutions in Porous Medium Systems

James E. McClure, Hao Wang, Jan F. Prins, Cass T. Miller, Wu-chun Feng

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Tags: Algorithms, CUDA, Fluid dynamics, Heterogeneous systems, Lattice Boltzmann model, MPI, nVidia, Tesla K20

May 23, 2014 by hgpu

A combined MPI-CUDA parallel solution of linear and nonlinear Poisson-Boltzmann equation

Jose Colmenares, Antonella Galizia, Jesus Ortiz, Andrea Clematis, Walter Rocchia

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Tags: Algorithms, Biology, Boltzmann equation, CUDA, Electrostatic potential, Electrostatics, Heterogeneous systems, Macromolecule, MPI, nVidia, nVidia GeForce GTX 580, Poisson Boltzmann, Tesla C2075

May 21, 2014 by hgpu

Exploiting Parallelism in GPUs

Blake Alan Hechtman

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Thesis

May 20, 2014 by hgpu

StarPU-MPI: Task Programming over Clusters of Machines Enhanced with Accelerators

Cedric Augonnet, Olivier Aumage, Nathalie Furmento, Samuel Thibault, Raymond Namyst

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, OpenCL, Tesla M2070

May 18, 2014 by hgpu

Hierarchical Transparent Programming for Heterogeneous Computing

Yuri Torres de la Sierra

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, OpenCL, Thesis

May 17, 2014 by hgpu

Heterogeneity-aware Fault Tolerance using a Self-Organizing Runtime System

Mario Kicherer, Wolfgang Karl

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 560 Ti, Operating systems

May 17, 2014 by hgpu

Optimized Composition: Generating Efficient Code for Heterogeneous Systems from Multi-Variant Components, Skeletons and Containers

Christoph Kessler, Usman Dastgeer, Lu Li

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Optimization, Package, Review, Tesla C2050

May 15, 2014 by hgpu

Code Optimization and Performance Analysis of Oceanographic Software Package NEMO for GPGPU Systems

Plamenka Borovska, Desislava Ivanova

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Tags: CUDA, Earth and Space Sciences, Heterogeneous systems, nVidia, Tesla M2075

May 12, 2014 by hgpu

Automatic Scheduling of Compute Kernels Across Heterogeneous Architectures

Robert F. Lyerly

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Tags: Compilers, Computer science, Heterogeneous systems, Intel Xeon Phi, Machine learning, nVidia, OpenCL, OpenMP, Task scheduling, Tesla C2075

May 9, 2014 by hgpu

Managing the Topology of Heterogeneous Cluster Nodes with Hardware Locality (hwloc)

Brice Goglin

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, OpenMPI, Package, Xeon Phi

May 7, 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

Review of Memory/Cache Management Technologies used on Heterogeneous Computing Systems

An Extensible Component-based Approach to Simulation Systems on Heterogeneous Clusters

Petascale Application of a Coupled CPU-GPU Algorithm for Simulation and Analysis of Multiphase Flow Solutions in Porous Medium Systems

A combined MPI-CUDA parallel solution of linear and nonlinear Poisson-Boltzmann equation

Exploiting Parallelism in GPUs

StarPU-MPI: Task Programming over Clusters of Machines Enhanced with Accelerators

Hierarchical Transparent Programming for Heterogeneous Computing

Heterogeneity-aware Fault Tolerance using a Self-Organizing Runtime System

Optimized Composition: Generating Efficient Code for Heterogeneous Systems from Multi-Variant Components, Skeletons and Containers

Code Optimization and Performance Analysis of Oceanographic Software Package NEMO for GPGPU Systems

Automatic Scheduling of Compute Kernels Across Heterogeneous Architectures

Managing the Topology of Heterogeneous Cluster Nodes with Hardware Locality (hwloc)

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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