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Irregularity Mitigation and Portability Abstractions for Accelerated Sparse Matrix Factorization

Daniel Thürck

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Tags: Algorithms, Computer science, Factorization, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan V, OpenCL, Sparse matrix, Thesis

May 9, 2021 by hgpu

Efficacy of Images Versus Data Buffers: Optimizing Interactive Applications Utilizing OpenCL for Scientific Visualization

Donald W. Johnson, T. J. Jankun-Kelly

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Tags: AMD Radeon HD 7950, ATI, Computer science, Interactive application, OpenCL, Visualization

May 9, 2021 by hgpu

DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning

Sheldon Fung, Xuequan Lu, Chao Zhang, Chang-Tsun Li

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce RTX 2080 Ti, PyTorch

May 2, 2021 by hgpu

Enabling Energy-Efficient DNN Training on Hybrid GPU-FPGA Accelerators

Xin He, Jiawen Liu, Zhen Xie, Hao Chen, Guoyang Chen, Weifeng Zhang, Dong Li

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Tags: Computer science, Deep learning, Design space exploration, FPGA, Hybrid computing, nVidia, OpenCL, Tesla V100

May 2, 2021 by hgpu

Easy and Efficient Transformer: Scalable Inference Solution For large NLP mode

Gongzheng li, Yadong Xi, Jingzhen Ding, Duan Wang, Bai Liu, Changjie Fan, Xiaoxi Mao, Zeng Zhao

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Tags: Computer science, CUDA, NLP, nVidia, nVidia GeForce RTX 2080 Ti, Package, Tesla A100

May 2, 2021 by hgpu

tcFFT: Accelerating Half-Precision FFT through Tensor Cores

Binrui Li, Shenggan Cheng, James Lin

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Tags: Computer science, FFT, Mixed precision, nVidia, nVidia DGX-2, nVidia DGX-A100, Tesla V100

May 2, 2021 by hgpu

How to Train BERT with an Academic Budget

Peter Izsak, Moshe Berchansky, Omer Levy

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Tags: Artificial intelligence, Computer science, Deep learning, Machine learning, NLP, nVidia, nVidia GeForce GTX Titan V, Tesla V100

April 25, 2021 by hgpu

Deep Graph Learning for Program Analysis and System Optimization

Yao Xiao, Guixiang Ma, Nesreen K. Ahmed, Theodore L. Willke, Shahin Nazarian, Paul Bogdan

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Tags: Computer science, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 970, OpenCL

April 25, 2021 by hgpu

Ripple: Simplified Large-Scale Computation on Heterogeneous Architectures with Polymorphic Data Layout

Robert Clucas, Philip Blakely, Nikolaos Nikiforakis

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Tesla V100

April 25, 2021 by hgpu

CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU

Sijun Tan, Brian Knott, Yuan Tian, David J. Wu

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Tags: Computer science, CUDA, Deep learning, Linear Algebra, Machine learning, Neural networks, nVidia, Package, PyTorch, Security, Tesla V100

April 25, 2021 by hgpu

Performance Analysis and Optimization Opportunities for NVIDIA Automotive GPUs

Hamid Tabani, Fabio Mazzocchetti, Pedro Benedicte, Jaume Abella, Francisco J. Cazorla

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson TX2, Performance

April 25, 2021 by hgpu

SLATE port to AMD and Intel platforms

Ahmad Abdelfattah, Mohammed Al Farhan, Cade Brown, Mark Gates, Dalal Sukkari, Asim YarKhan, Jack Dongarra

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, OpenCL, Package, SYCL

April 18, 2021 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

Irregularity Mitigation and Portability Abstractions for Accelerated Sparse Matrix Factorization

Efficacy of Images Versus Data Buffers: Optimizing Interactive Applications Utilizing OpenCL for Scientific Visualization

DeepfakeUCL: Deepfake Detection via Unsupervised Contrastive Learning

Enabling Energy-Efficient DNN Training on Hybrid GPU-FPGA Accelerators

Easy and Efficient Transformer: Scalable Inference Solution For large NLP mode

tcFFT: Accelerating Half-Precision FFT through Tensor Cores

How to Train BERT with an Academic Budget

Deep Graph Learning for Program Analysis and System Optimization

Ripple: Simplified Large-Scale Computation on Heterogeneous Architectures with Polymorphic Data Layout

CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU

Performance Analysis and Optimization Opportunities for NVIDIA Automotive GPUs

SLATE port to AMD and Intel platforms

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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