Making Powerful Enemies on NVIDIA GPUs-Reference-Cited by-同舟云学术

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Making Powerful Enemies on NVIDIA GPUs

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Real-Time Systems Symposium (RTSS)
language:
Short-container-title:

Author:

Yandrofski Tyler¹,Chen Jingyuan¹,Otterness Nathan¹,Anderson James H.¹,Smith F. Donelson¹

Affiliation:

1. University of North Carolina at Chapel Hill,Department of Computer Science

Funder

NSF

ARO

ONR

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9984704/9984706/09984754.pdf?arnumber=9984754

Reference41 articles.

1. Slow and steady: Measuring and tuning multicore interference;iorga;IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS),0

2. Avoiding pitfalls when using NVIDIA GPUs for real-time tasks in autonomous systems;yang;Euromicro Conference on Real-Time Systems (ECRTS),0

3. A Unified WCET analysis framework for multicore platforms

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Uso de GPUs en aplicaciones de tiempo real: Una revisión de técnicas para el análisis y optimización de parámetros temporales;Revista Iberoamericana de Automática e Informática industrial;2023-11-07

2. Hardware Compute Partitioning on NVIDIA GPUs*;2023 IEEE 29th Real-Time and Embedded Technology and Applications Symposium (RTAS);2023-05

3. Memory-Aware Latency Prediction Model for Concurrent Kernels in Partitionable GPUs: Simulations and Experiments;Job Scheduling Strategies for Parallel Processing;2023

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