high performance computing on graphics processing units: hgpu.org

hgpu.org » Memory

A Locality-Aware Memory Hierarchy for Energy-Efficient GPU Architectures

Minsoo Rhu, Michael Sullivan, Jingwen Leng, Mattan Erez

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

October 29, 2013 by hgpu

Cudagrind: A Valgrind Extension for CUDA

Thomas M. Baumann, Jose Gracia

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Source codes

Tags: Computer science, CUDA, Memory, nVidia, Package, Software Engineering

October 4, 2013 by hgpu

Optimization solutions for the segmented sum algorithmic function

Alexandru Pirjan

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Performance

September 21, 2013 by hgpu

Optimal Configuration of GPU Cache Memory to Maximize the Performance

Leonid Djinevski, Sime Arsenovski, Sasko Ristov, Marjan Gusev

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, Memory, nVidia, nVidia GeForce GTX 680, Performance

September 16, 2013 by hgpu

Histogram Computations on GPUs Kernel using Global and Shared Memory Atomics

C.P.Patidar, Meena Sharma

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GT 610

September 11, 2013 by hgpu

D5.5.2 – Architectural Techniques to exploit SLACK & ACCURACY trade-offs

S. Kaxiras, G. Keramidas, K. Koukos

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Tags: Benchmarking, Memory, Power-efficient computing

September 6, 2013 by hgpu

Phase Aware Memory Scheduling

C. Sangani, M. Venkatesan, R. Ramesh

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Tags: Heterogeneous systems, Memory, Memory model

September 6, 2013 by hgpu

An Energy Efficient GPGPU Memory Hierarchy with Tiny Incoherent Caches

Alamelu Sankaranarayanan, Ehsan K. Ardestani, Jose Luis Briz, Jose Renau

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Tags: Computer science, CUDA, Energy-efficient computing, GPGPU-sim, Memory, nVidia, OpenCL

June 24, 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

An Implementation of Conflict-Free Offline Permutation on the GPU

Akihiko Kasagi, Koji Nakano, Yasuaki Ito

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Tags: Computer science, CUDA, Memory, Memory model, nVidia, nVidia GeForce GTX 680, Performance

February 6, 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

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

A Locality-Aware Memory Hierarchy for Energy-Efficient GPU Architectures

Cudagrind: A Valgrind Extension for CUDA

Optimization solutions for the segmented sum algorithmic function

Optimal Configuration of GPU Cache Memory to Maximize the Performance

Histogram Computations on GPUs Kernel using Global and Shared Memory Atomics

D5.5.2 – Architectural Techniques to exploit SLACK & ACCURACY trade-offs

Phase Aware Memory Scheduling

An Energy Efficient GPGPU Memory Hierarchy with Tiny Incoherent Caches

Warp Size Impact in GPUs: Large or Small?

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

An Implementation of Conflict-Free Offline Permutation on the GPU

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

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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