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Parallel GPU Architecture Simulation Framework Exploiting Work Allocation Unit Parallelism

Sangpil Lee, Won Woo Ro

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 285

April 17, 2013 by hgpu

Warp Size Impact in GPUs: Large or Small?

Ahmad Lashgar, Amirali Baniasadi, Ahmad Khonsari

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Tags: Computer science, GPGPU-sim, Memory, Performance

March 29, 2013 by hgpu

Can PCM Benefit GPU? Reconciling Hybrid Memory Design with GPU Massive Parallelism for Energy Efficiency

Bin Wang, Bo Wu, Dong Li, Xipeng Shen, Weikuan Yu, Yizheng Jiao, Jeffrey Vetter

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Tags: Computer science, GPGPU-sim, Memory, Performance

February 23, 2013 by hgpu

The Dual-Path Execution Model for Efficient GPU Control Flow

Minsoo Rhu, Mattan Erez

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, Performance

February 14, 2013 by hgpu

Survey On The Off-Chip Scheduling of Memory Accesses in the Memory Interface Of GPUs

Luis Angel Garrido Platero

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, Memory, nVidia, Performance

January 31, 2013 by hgpu

GPUDet: A Deterministic GPU Architecture

Hadi Jooybar, Wilson W. L. Fung, Mike O'Connor, Joseph Devietti, Tor M. Aamodt

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Tags: Computer science, GPGPU-sim, Hardware Architecture, nVidia, nVidia GeForce GTX 480

January 29, 2013 by hgpu

Warped Register File: A Power Efficient Register File for GPGPUs

Mohammad Abdel-Majeed, Murali Annavaram

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, Performance

January 28, 2013 by hgpu

Inter-Warp Instruction Temporal Locality in Deep-Multithreaded GPUs

Ahmad Lashgar, Amirali Baniasadi, Ahmad Khonsari

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Tags: Computer science, Energy-efficient computing, GPGPU-sim, nVidia, Tesla

January 17, 2013 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

Parallel GPU Architecture Simulation Framework Exploiting Work Allocation Unit Parallelism

Warp Size Impact in GPUs: Large or Small?

Can PCM Benefit GPU? Reconciling Hybrid Memory Design with GPU Massive Parallelism for Energy Efficiency

The Dual-Path Execution Model for Efficient GPU Control Flow

Survey On The Off-Chip Scheduling of Memory Accesses in the Memory Interface Of GPUs

GPUDet: A Deterministic GPU Architecture

Warped Register File: A Power Efficient Register File for GPGPUs

Inter-Warp Instruction Temporal Locality in Deep-Multithreaded GPUs

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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