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Energy-efficient Computing on Distributed GPUs using Dynamic Parallelism and GPU-controlled Communication

Lena Oden, Benjamin Klenk, Holger Froning

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Tags: Cluster computing, Computer science, CUDA, Distributed computing, Energy-efficient computing, GPU cluster, nVidia, Tesla K20

March 25, 2015 by hgpu

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming

Kamran Karimi

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Tags: ATI, Computer science, OpenCL, OpenMP, Performance

March 25, 2015 by hgpu

Data driven scheduling approach for the multi-node multi-GPU Cholesky decomposition

Yuki Tsujita, Toshio Endo

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Tags: Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Task scheduling, Tesla K20

March 25, 2015 by hgpu

Curracurrong: a stream processing system for distributed environments

Vasvi Kakkad

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Tags: Algorithms, Computer science, CUDA, OpenCL, Thesis

March 23, 2015 by hgpu

Massively Parallel Construction of the Cell Graph

Krzysztof Kaczmarski, Pawel Rzazewski, Albert Wolant

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Tags: Algorithms, Computer science, CUDA, nVidia, Robotics, Tesla K40

March 23, 2015 by hgpu

A Financial Benchmark for GPGPU Compilation

Christian Andreetta, Vivien Begot, Jost Berthold, Martin Elsman, Troels Henriksen, Maj-Britt Nordfang, Cosmin E. Oancea

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Tags: Benchmarking, Computer science, CUDA, Finance, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 780 Ti

March 23, 2015 by hgpu

PTX2Kernel: Converting PTX Code into Compilable Kernels

Qiankun Dong, Tao Li, Shuai Zhang, Xiaofan Jiao, Jiabing Leng

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 480, PTX, Tesla K40

March 22, 2015 by hgpu

Speeding Up Computer Vision Applications on Mobile Computing Platforms

Luna Backes

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Tags: Computer science, Computer vision, nVidia, OpenCL, Thesis

March 22, 2015 by hgpu

Raising the Bar for Using GPUs in Software Packet Processing

Anuj Kalia, Dong Zhou, Michael Kaminsky, David G. Andersen

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 650 Ti, nVidia GeForce GTX 980, Performance, Tesla K20

March 22, 2015 by hgpu

Single stream parallelization of generalized LSTM-like RNNs on a GPU

Kyuyeon Hwang, Wonyong Sung

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Tags: Algorithms, Computer science, CUDA, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K40

March 22, 2015 by hgpu

CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication

Weifeng Liu, Brian Vinter

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Tags: Algorithms, AMD Radeon R9 290X, Benchmarking, Computer science, CUDA, Intel Xeon Phi, Mathematical Software, nVidia, nVidia GeForce GTX 980, OpenCL, Package, Performance, Sparse matrix

March 20, 2015 by hgpu

Interactive Illustrative Line Styles and Line Style Transfer Functions for Flow Visualization

Maarten H. Everts, Henk Bekker, Jos B.T.M. Roerdink, Tobias Isenberg

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Tags: Computer science, Graphics, nVidia, nVidia GeForce GTX 285, Visualization

March 20, 2015 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

Energy-efficient Computing on Distributed GPUs using Dynamic Parallelism and GPU-controlled Communication

The Feasibility of Using OpenCL Instead of OpenMP for Parallel CPU Programming

Data driven scheduling approach for the multi-node multi-GPU Cholesky decomposition

Curracurrong: a stream processing system for distributed environments

Massively Parallel Construction of the Cell Graph

A Financial Benchmark for GPGPU Compilation

PTX2Kernel: Converting PTX Code into Compilable Kernels

Speeding Up Computer Vision Applications on Mobile Computing Platforms

Raising the Bar for Using GPUs in Software Packet Processing

Single stream parallelization of generalized LSTM-like RNNs on a GPU

CSR5: An Efficient Storage Format for Cross-Platform Sparse Matrix-Vector Multiplication

Interactive Illustrative Line Styles and Line Style Transfer Functions for Flow Visualization

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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