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Survey paper on Deep Learning on GPUs

Sparsh Mittal, Shraiysh Vaishay

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Tags: Deep learning, Paper, Research, survey

August 21, 2019 by sparsh0mittal

A Survey on Evaluating and Optimizing Performance of Intel Xeon Phi

Sparsh Mittal, Osho Anand, Visnu P Kumarr

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Tags: Compilers, Computer science, Intel Xeon Phi, OpenMP, survey

June 9, 2019 by hgpu

A Survey on Optimized Implementation of Deep Learning Models on the NVIDIA Jetson Platform

Sparsh Mittal

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia Jetson TK1, nVidia Jetson TX1, nVidia Jetson TX2, OpenCL, survey

December 30, 2018 by hgpu

A Survey of FPGA-based Accelerators for Convolutional Neural Networks

Sparsh Mittal

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Tags: Algorithms, Artificial intelligence, Computer science, Deep learning, FPGA, HLS, Neural networks, OpenCL, survey

October 21, 2018 by hgpu

A Survey of ReRAM-based Architectures for Processing-in-memory and Neural Networks

Sparsh Mittal

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Tags: Machine learning, memristor, neural network, processing in memory, survey

May 5, 2018 by sparsh0mittal

A Survey of Techniques for Dynamic Branch Prediction

Sparsh Mittal

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Tags: branch predictor, Paper, speculative execution, survey

April 25, 2018 by sparsh0mittal

A Survey of Techniques for Improving Security of GPUs

Sparsh Mittal, S.B. Abhinaya, Manish Reddy, Irfan Ali

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Tags: Computer science, Security, survey

April 7, 2018 by hgpu

Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

Stylianos I. Venieris, Alexandros Kouris, Christos-Savvas Bouganis

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Tags: Artificial intelligence, Computer science, Deep learning, Design space exploration, FPGA, OpenCL, survey

March 17, 2018 by hgpu

A Survey of Techniques for Improving Security of Non-volatile Memories

Sparsh Mittal, Ahmed Alsalibi

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Tags: Computer science, Hardware security, non-volatile memory, Security, survey

February 15, 2018 by sparsh0mittal

Graph Processing on GPUs: A Survey

Xuanhua Shi, Zhigao Zheng, Yongluan Zhou, Hai Jin, Ligang He, Bo Liu, Qiang-Sheng Hua

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Tags: Computer science, CUDA, Graph theory, nVidia, OpenCL, survey

January 13, 2018 by hgpu

Sorting with GPUs: A Survey

Dmitri I. Arkhipov, Di Wu, Keqin Li, Amelia C. Regan

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Tags: Algorithms, Computer science, CUDA, nVidia, Sorting, survey

September 12, 2017 by hgpu

A Survey of Techniques for Architecting TLBs

Sparsh Mittal

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Tags: cpu, CPU-GPU system, GPU, Power management, survey, TLB, virtual memory

November 2, 2016 by sparsh0mittal

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

Survey paper on Deep Learning on GPUs

A Survey on Evaluating and Optimizing Performance of Intel Xeon Phi

A Survey on Optimized Implementation of Deep Learning Models on the NVIDIA Jetson Platform

A Survey of FPGA-based Accelerators for Convolutional Neural Networks

A Survey of ReRAM-based Architectures for Processing-in-memory and Neural Networks

A Survey of Techniques for Dynamic Branch Prediction

A Survey of Techniques for Improving Security of GPUs

Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions

A Survey of Techniques for Improving Security of Non-volatile Memories

Graph Processing on GPUs: A Survey

Sorting with GPUs: A Survey

A Survey of Techniques for Architecting TLBs

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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