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Work-In-Progress: Protecting Real-Time GPU Applications on Integrated CPU-GPU SoC Platforms

https://doi.org/10.1109/rtas.2017.26

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1109/cvpr.2001.990517openalex-snapshot

Rapid object detection using a boosted cascade of simple features

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An Open Approach to Autonomous Vehicles

inferredcites →https://doi.org/10.1109/rtas.2015.7108420openalex-snapshot

GPES: a preemptive execution system for GPGPU computing

inferredcites →https://doi.org/10.1109/rtas.2016.7461361openalex-snapshot

Taming Non-Blocking Caches to Improve Isolation in Multicore Real-Time Systems

inferredcites →https://doi.org/10.1109/rtas.2017.3openalex-snapshot

An Evaluation of the NVIDIA TX1 for Supporting Real-Time Computer-Vision Workloads

inferredcites →https://doi.org/10.1109/tc.2016.2640961openalex-snapshot

BWLOCK: A Dynamic Memory Access Control Framework for Soft Real-Time Applications on Multicore Platforms

inferredcites →https://doi.org/10.1145/2694344.2694381openalex-snapshot

Page Placement Strategies for GPUs within Heterogeneous Memory Systems

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/spe.2840openalex-snapshot

Timing isolation and improved scheduling of deep neural networks for real‐time systems

inferred← citeshttps://doi.org/10.1016/j.sysarc.2022.102416openalex-snapshot

Optimized partitioning and priority assignment of real-time applications on heterogeneous platforms with hardware acceleration

inferred← citeshttps://doi.org/10.1109/iecon.2018.8591540openalex-snapshot

A Perspective on Safety and Real-Time Issues for GPU Accelerated ADAS

inferred← citeshttps://doi.org/10.1109/rtss.2018.00021openalex-snapshot

Deadline-Based Scheduling for GPU with Preemption Support

inferred← citeshttps://doi.org/10.1109/rtss46320.2019.00042openalex-snapshot

Pipelined Data-Parallel CPU/GPU Scheduling for Multi-DNN Real-Time Inference

inferred← citeshttps://doi.org/10.1109/tc.2020.2980520openalex-snapshot

HePREM: A Predictable Execution Model for GPU-based Heterogeneous SoCs

inferred← citeshttps://doi.org/10.1109/tcad.2020.3012210openalex-snapshot

Dynamic Memory Bandwidth Allocation for Real-Time GPU-Based SoC Platforms

inferred← citeshttps://doi.org/10.1109/tcad.2025.3616847openalex-snapshot

REEG: Reinforcement Learning-Based Gang Scheduling in Multicore Embedded Systems

inferred← citeshttps://doi.org/10.1145/3341105.3373866openalex-snapshot

GPU swap-aware scheduler

inferred← citeshttps://doi.org/10.1145/3548773openalex-snapshot

Evaluating Controlled Memory Request Injection for Efficient Bandwidth Utilization and Predictable Execution in Heterogeneous SoCs

inferred← citeshttps://doi.org/10.1145/3803800openalex-snapshot

Real-Time Task Mapping for CPU-GPU Heterogeneous Platforms: Spatial GPU Partitioning and Utilization Bound

inferred← citeshttps://doi.org/10.23919/date.2019.8715255openalex-snapshot

Taming Data Caches for Predictable Execution on GPU-based SoCs

inferred← citeshttps://doi.org/10.4995/riai.2023.20321openalex-snapshot

Uso de GPUs en aplicaciones de tiempo real: Una revisión de técnicas para el análisis y optimización de parámetros temporales

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