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Flexible Performant GEMM Kernels on GPUs

Thomas Faingnaert, Tim Besard, Bjorn De Sutter

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Tags: Computer science, CUBLAS, CUDA, Julia, Machine learning, Mathematical Software, Matrix multiplication, Mixed precision, nVidia, nVidia GeForce RTX 2080 Ti, Package, Performance

October 4, 2020 by hgpu

Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores

Orestis Zachariadis, Nitin Satpute, Juan Gómez-Luna, Joaquín Olivares

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, Mixed precision, nVidia, nVidia GeForce RTX 2070, nVidia Titan RTX, Package, Performance, Sparse matrix

October 4, 2020 by hgpu

Extending High-Level Synthesis for Task-Parallel Programs

Yuze Chi, Licheng Guo, Young-kyu Choi, Jie Wang, Jason Cong

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Tags: Code generation, Computer science, FPGA, HLS, OpenCL, Package

September 27, 2020 by hgpu

Performance Evaluation of Mixed Precision Algorithms for Solving Sparse Linear Systems

Mawussi Zounon, Nicholas J. Higham, Craig Lucas, Françoise Tisseur

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Tags: Algorithms, Computer science, CUDA, Factorization, Mixed precision, nVidia, Tesla P100, Tesla V100

September 27, 2020 by hgpu

Adaptation of High Performance and High Capacity Reconfigurable Systems to OpenCL Programming Environments

Davide Russo

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

September 27, 2020 by hgpu

Applications of Deep Neural Networks

Jeff Heaton

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Tags: Book, Computer science, Computer vision, Deep learning, Neural networks, NLP, Package, Python, Security

September 20, 2020 by hgpu

Designing Efficient Barriers and Semaphores for Graphics Processing Units

Rohan Mahapatra

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX Titan V, nVidia GeForce RTX 2080 Ti, Thesis

September 20, 2020 by hgpu

A Comparison of Optimal Scanline Voxelization Algorithms

Tim Håkansson

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Tags: 3D Graphics and Realism, CUDA, GLSL, nVidia, OpenGL, Package, Tesla T4, Thesis, Voxelization

September 20, 2020 by hgpu

WarpCore: A Library for fast Hash Tables on GPUs

Daniel Jünger, Robin Kobus, André Müller, Christian Hundt, Kai Xu, Weiguo Liu, Bertil Schmidt

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Tags: Bioinformatics, Computer science, CUDA, Hashing, nVidia, nVidia Quadro GV100, Tesla V100

September 20, 2020 by hgpu

PySchedCL: Leveraging Concurrency in Heterogeneous Data-Parallel Systems

Anirban Ghose, Siddharth Singh, Vivek Kulaharia, Lokesh Dokara, Srijeeta Maity, Soumyajit Dey

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Tags: Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 970, OpenCL, Package

September 20, 2020 by hgpu

Tools for GPU Computing–Debugging and Performance Analysis of Heterogenous HPC Applications

Michael Knobloch, Bernd Mohr

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Tags: Computer science, CUDA, nVidia, OpenCL, Performance, survey

September 13, 2020 by hgpu

Accelerating High-Order Stencils on GPUs

Ryuichi Sai, John Mellor-Crummey, Xiaozhu Meng, Mauricio Araya-Polo, Jie Meng

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Tags: Computer science, HPC, nVidia, nVidia Quadro NVS 510, Package, Performance, Stencil computation, Tesla P100, Tesla V100

September 13, 2020 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

Applications

Flexible Performant GEMM Kernels on GPUs

Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores

Extending High-Level Synthesis for Task-Parallel Programs

Performance Evaluation of Mixed Precision Algorithms for Solving Sparse Linear Systems

Adaptation of High Performance and High Capacity Reconfigurable Systems to OpenCL Programming Environments

Applications of Deep Neural Networks

Designing Efficient Barriers and Semaphores for Graphics Processing Units

A Comparison of Optimal Scanline Voxelization Algorithms

WarpCore: A Library for fast Hash Tables on GPUs

PySchedCL: Leveraging Concurrency in Heterogeneous Data-Parallel Systems

Tools for GPU Computing–Debugging and Performance Analysis of Heterogenous HPC Applications

Accelerating High-Order Stencils on GPUs

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

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