high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

ThunderSVM: A Fast SVM Library on GPUs and CPUs

Zeyi Wen, Jiashuai Shi, Bingsheng He, Qinbin Li, Jian Chen

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Tags: Computer science, CUDA, Data mining, Machine learning, nVidia, OpenMP, Package, Tesla P100

January 6, 2018 by hgpu

Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer

Amrita Mathuriya, Thorsten Kurth, Vivek Rane, Mustafa Mustafa, Lei Shao, Debbie Bard, Prabhat, Victor W Lee

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Tags: Benchmarking, Computer science, Deep learning, Intel Xeon Phi, Neural networks, Performance, TensorFlow

January 6, 2018 by hgpu

Analysing the Performance of GPU Hash Tables for State Space Exploration

Nathan Cassee, Anton Wijs

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Tags: Computer science, CUDA, Design space exploration, Hashing, nVidia, nVidia GeForce GT 750 M, Performance

January 6, 2018 by hgpu

Using reconfigurable computing technology to accelerate matrix decomposition and applications

Xinying Wang

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Tags: Computer science, Data mining, Factorization, FPGA, Intel Xeon Phi, Matrix decomposition, Semantic indexing, Signal processing, Text mining, Thesis

December 28, 2017 by hgpu

Design and Implementation of the Futhark Programming Language

Troels Henriksen

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Tags: AMD FirePro W8100, ATI, Computer science, Haskell, High-level Languages, nVidia, OpenCL, Package, Tesla K40, Thesis

December 28, 2017 by hgpu

A Survey of FPGA Based Neural Network Accelerator

Kaiyuan Guo, Shulin Zeng, Jincheng Yu, Yu Wang, Huazhong Yang

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Tags: Computer science, Computer vision, FPGA, Machine learning, Neural networks

December 28, 2017 by hgpu

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

Waqar Ali, Heechul Yun

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Tags: Computer science, CUDA, nVidia, nVidia Jetson TK1, Operating systems, Performance, Security, SoC

December 28, 2017 by hgpu

A Generic Inverted Index Framework for Similarity Search on the GPU

Jingbo Zhou, Qi Guo, H. V. Jagadish, Lubos Krcal, Siyuan Liu, Wenhao Luan, Anthony K. H. Tung, Yueji Yang, Yuxin Zheng

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Tags: Computer science, CUDA, Hashing, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan X, OpenMPI, Package

December 28, 2017 by hgpu

Pass a Pointer: Exploring Shared Virtual Memory Abstractions in OpenCL Tools for FPGAs

Felix Winterstein, George Constantinides

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

December 24, 2017 by hgpu

Extending OmpSs for OpenCL kernel co-execution in heterogeneous systems

B. Perez, E. Stafford, J. L. Bosque, R. Beivide, S. Mateo, X. Teruel, X. Martorell, E. Ayguade

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Tags: Algorithms, Computer science, Heterogeneous systems, nVidia, OmpSs, OpenCL, OpenMP, Tesla K20

December 24, 2017 by hgpu

An MPI-Based Python Framework for Distributed Training with Keras

Dustin Anderson, Jean-Roch Vlimant, Maria Spiropulu

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Tags: Computer science, CUDA, Deep learning, Keras, Machine learning, MPI, Neural networks, nVidia, nVidia GeForce GTX 1080, Package, Python, Tesla K80

December 24, 2017 by hgpu

An In-depth Performance Characterization of CPU- and GPU-based DNN Training on Modern Architectures

Ammar Ahmad Awan, Hari Subramoni, Dhabaleswar K. Panda

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Tags: Benchmarking, Caffe, Computer science, CUBLAS, CUDA, Deep learning, Intel Xeon Phi, Machine learning, nVidia, Tela K40, Tesla K80, Tesla P100

December 24, 2017 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Applications

ThunderSVM: A Fast SVM Library on GPUs and CPUs

Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer

Analysing the Performance of GPU Hash Tables for State Space Exploration

Using reconfigurable computing technology to accelerate matrix decomposition and applications

Design and Implementation of the Futhark Programming Language

A Survey of FPGA Based Neural Network Accelerator

Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

A Generic Inverted Index Framework for Similarity Search on the GPU

Pass a Pointer: Exploring Shared Virtual Memory Abstractions in OpenCL Tools for FPGAs

Extending OmpSs for OpenCL kernel co-execution in heterogeneous systems

An MPI-Based Python Framework for Distributed Training with Keras

An In-depth Performance Characterization of CPU- and GPU-based DNN Training on Modern Architectures

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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