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Parameterized Verification of GPU Kernel Programs

Guodong Li, Ganesh Gopalakrishnan

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Tags: Computer science, CUDA, nVidia, Optimization

May 26, 2012 by hgpu

Parallel Parametric Optimisation with Firefly Algorithms on Graphical Processing Units

A.V. Husselmann, K.A. Hawick

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 590, Optimization

May 26, 2012 by hgpu

On the Simulations of Evolution-Communication P Systems with Energy without Antiport Rules for GPUs

Richelle Ann B. Juayong, Francis George C. Cabarle, Henry N. Adorna, Miguel A. Martinez-del-Amor

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Tags: Computer science, CUDA, Membrane computing, nVidia, P systems

May 25, 2012 by hgpu

Effective Sparse Matrix Representation for the GPU Architectures

B. Neelima, Prakash S. Raghavendra

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 525 M, Optimization, Sparse matrix

May 25, 2012 by hgpu

Accelerating In-Memory Graph Database traversal using GPGPUS

Ashwin Raghav Mohan Ganesh

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Tags: Computer science, CUDA, Databases, nVidia, Package

May 25, 2012 by hgpu

Parallel simulation of mixed-abstraction SystemC models on GPUs and multicore CPUs

Rohit Sinha, Aayush Prakash, Hiren D. Patel

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Tags: Computer science, CUDA, nVidia, Tesla C2075

May 25, 2012 by hgpu

Java on CUDA architecture

Jan Strnad

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Tags: Computer science, CUDA, Image processing, Java, Linear Algebra, Matrix multiplication, nVidia, Thesis

May 24, 2012 by hgpu

Sparse direct solvers with accelerators over DAG runtimes

Xavier Lacoste, Pierre Ramet, Mathieu Faverge, Yamazaki Ichitaro, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Sparse direct solvers, Tesla T20

May 24, 2012 by hgpu

Tuning a Finite Difference Computation for Parallel Vector Processors

Gerhard Zumbusch

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Tags: Algorithms, Computer science, Finite difference, nVidia, nVidia GeForce GT 540 M, nVidia GeForce GTX 480, nVidia GeForce GTX 680, OpenCL, Performance

May 24, 2012 by hgpu

Compiler optimizations for directive-based programming for accelerators

Matias Piispanen

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Optimization

May 24, 2012 by hgpu

Fine-Grained Resource Sharing for Concurrent GPGPU Kernels

Chris Gregg, Jonathan Dorn, Kim Hazelwood, Kevin Skadron

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Tags: Computer science, nVidia, nVidia GeForce GTX 460, OpenCL, Programming techniques, Task scheduling

May 24, 2012 by hgpu

GMProf: A Low-Overhead, Fine-Grained Profiling Approach for GPU Programs

Mai Zheng, Vignesh T. Ravi, Wenjing Ma, Feng Qin, Gagan Agrawal

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Tags: Computer science, CUDA, nVidia, Optimization, Performance, Tesla C1060

May 23, 2012 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

Parameterized Verification of GPU Kernel Programs

Parallel Parametric Optimisation with Firefly Algorithms on Graphical Processing Units

On the Simulations of Evolution-Communication P Systems with Energy without Antiport Rules for GPUs

Effective Sparse Matrix Representation for the GPU Architectures

Accelerating In-Memory Graph Database traversal using GPGPUS

Parallel simulation of mixed-abstraction SystemC models on GPUs and multicore CPUs

Java on CUDA architecture

Sparse direct solvers with accelerators over DAG runtimes

Tuning a Finite Difference Computation for Parallel Vector Processors

Compiler optimizations for directive-based programming for accelerators

Fine-Grained Resource Sharing for Concurrent GPGPU Kernels

GMProf: A Low-Overhead, Fine-Grained Profiling Approach for GPU Programs

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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