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Anatomy of High-Performance GEMM with Online Fault Tolerance on GPUs

Shixun Wu, Yujia Zhai, Jinyang Liu, Jiajun Huang, Zizhe Jian, Bryan M. Wong, Zizhong Chen

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Tags: Code generation, Computer science, CUDA, GEMM, Linear Algebra, Matrix multiplication, nVidia, nVidia A100, Package, Performance, Reliability, Tesla T4

May 7, 2023 by hgpu

A Survey of Soft-Error Mitigation Techniques for Non-Volatile Memories

Sparsh Mittal

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Tags: classification, Memory, Reliability, Review

February 19, 2017 by sparsh0mittal

Design and Analysis of Soft-Error Resilience Mechanisms for GPU Register File

Sparsh Mittal, Haonan Wang, Adwait Jog and Jeffrey Vetter

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Tags: GPU, Register file, Reliability

November 1, 2016 by sparsh0mittal

A Survey of Techniques for Architecting Processor Components using Domain Wall Memory

Sparsh Mittal

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Tags: cache, cpu, energy, GPU, main memory, Performance, Register file, Reliability

September 5, 2016 by sparsh0mittal

A Survey of Techniques for Architecting and Managing GPU Register File

Sparsh Mittal

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Tags: Energy efficiency, GPU, nVidia, Performance, Power, Register file, Reliability, Research, survey

March 22, 2016 by sparsh0mittal

A Survey of Techniques for Modeling and Improving Reliability of Computing Systems

Sparsh Mittal, Jeffrey Vetter

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Tags: cache, cpu, Fault tolerance, GPU, main memory, non-volatile memory, Reliability, resilience, vulnerability

April 21, 2015 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

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

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

Anatomy of High-Performance GEMM with Online Fault Tolerance on GPUs

A Survey of Soft-Error Mitigation Techniques for Non-Volatile Memories

Design and Analysis of Soft-Error Resilience Mechanisms for GPU Register File

A Survey of Techniques for Architecting Processor Components using Domain Wall Memory

A Survey of Techniques for Architecting and Managing GPU Register File

A Survey of Techniques for Modeling and Improving Reliability of Computing Systems

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

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

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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