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GGArray: A Dynamically Growable GPU Array

Enzo meneses, Cristóbal A. Navarro, Héctor Ferrada

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Tags: Algorithms, Computer science, CUDA, Memory, nVidia, nVidia A100, nVidia Titan RTX

September 4, 2022 by hgpu

Memory Optimization for Deep Networks

Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl

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Tags: Computer science, CUDA, Deep learning, Memory, nVidia, Optimization, Package, PyTorch, Tesla P100

November 1, 2020 by hgpu

Bounds Checking on GPU

Troels Henriksen

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Performance

August 2, 2020 by hgpu

UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

Yongbin Gu, Wenxuan Wu, Yunfan Li, Lizhong Chen

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 1080 Ti, Package, Performance

July 26, 2020 by hgpu

Characterizing Optimizations to Memory Access Patterns using Architecture-Independent Program Features

Aditya Chilukuri, Josh Milthorpe, Beau Johnston

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Tags: Computer science, Heterogeneous systems, Memory, nVidia, OpenCL, Performance, Tesla P100

March 29, 2020 by hgpu

Performance Evaluation of Advanced Features in CUDA Unified Memory

Steven W. D. Chien, Ivy B. Peng, Stefano Markidis

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 1050, Package, Prefetch, Tesla V100

October 27, 2019 by hgpu

The Memory Controller Wall: Benchmarking the Intel FPGA SDK for OpenCL Memory Interface

Hamid Reza Zohouri, Satoshi Matsuoka

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Tags: Benchmarking, Computer science, FPGA, HLS, Memory, nVidia, OpenCL, Package, Tesla K20, Tesla V100

October 20, 2019 by hgpu

A Survey of Techniques for Architecting SLC/MLC/TLC Hybrid Flash Memory based SSDs

Ahmed I Alsalibi, Sparsh Mittal, Mohammed Azmi Al-betar and Putra Bin Sumari

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Tags: Flash memory, Memory

December 14, 2017 by sparsh0mittal

Capability Models for Manycore Memory Systems: A Case-Study with Xeon Phi KNL

Sabela Ramos, Torsten Hoefler

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Tags: Computer science, Intel Xeon Phi, Memory, MPI, OpenMP

April 20, 2017 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

Data Remanence and Digital Forensic Investigation for CUDA Graphics Processing Units

X. J. A. Bellekens, G. Paul, J. M. Irvine, C. Tachtatzis, R. C. Atkinson, C. Renfrew, T. Kirkham

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Tags: Computer science, data leak, Data recovery, forensic, GPU, Memory, remanence, vulnerable

May 28, 2016 by xhgpu

A Graph-based Model for GPU Caching Problems

Lingda Li, Ari B. Hayes, Stephen A. Hackler, Eddy Z. Zhang, Mario Szegedy, Shuaiwen Leon Song

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 680, Task scheduling

May 9, 2016 by hgpu

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Beehive SPIR-V Toolkit

Experiences in Building a Composable and Functional API for Runtime SPIR-V Code Generation

TorchBench: a collection of open source benchmarks used to evaluate PyTorch performance

TorchBench: Benchmarking PyTorch with High API Surface Coverage

Prediction of Performance and Power Consumption of GPGPU Applications

Descend: an attempt at safe imperative GPU programming

Descend: A Safe GPU Systems Programming Language

Redwood heterogeneous framework

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

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high performance computing on graphics processing units: hgpu.org

GGArray: A Dynamically Growable GPU Array

Memory Optimization for Deep Networks

Bounds Checking on GPU

UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

Characterizing Optimizations to Memory Access Patterns using Architecture-Independent Program Features

Performance Evaluation of Advanced Features in CUDA Unified Memory

The Memory Controller Wall: Benchmarking the Intel FPGA SDK for OpenCL Memory Interface

A Survey of Techniques for Architecting SLC/MLC/TLC Hybrid Flash Memory based SSDs

Capability Models for Manycore Memory Systems: A Case-Study with Xeon Phi KNL

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

Data Remanence and Digital Forensic Investigation for CUDA Graphics Processing Units

A Graph-based Model for GPU Caching Problems

Recent source codes

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

AutoDock for GPUs and other accelerators

spotPython: Sequential Parameter Optimization in Python

Test benchmarks for CELERITY

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Beehive SPIR-V Toolkit

TorchBench: a collection of open source benchmarks used to evaluate PyTorch performance

Prediction of Performance and Power Consumption of GPGPU Applications

Descend: an attempt at safe imperative GPU programming

Redwood heterogeneous framework

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