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An Evaluation of the NVIDIA TX1 for Supporting Real-Time Computer-Vision Workloads
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Batch Method for Efficient Resource Sharing in Real-Time Multi-GPU Systems
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Makespan Computation for GPU Threads Running on a Single Streaming Multiprocessor
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Estimating the WCET of GPU-Accelerated Applications Using Hybrid Analysis
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OUTSTANDING PAPER: Evaluation of Cache Partitioning for Hard Real-Time Systems
inferredcites →https://doi.org/10.1109/etfa.2013.6647966openalex-snapshot
Faster makespan estimation for GPU threads on a single streaming multiprocessor
inferredcites →https://doi.org/10.1109/icccn.2014.6911778openalex-snapshot
Scheduling periodic real-time communication in multi-GPU systems
inferredcites →https://doi.org/10.1109/ispass.2010.5452013openalex-snapshot
Demystifying GPU microarchitecture through microbenchmarking
inferredcites →https://doi.org/10.1109/rtas.2015.7108420openalex-snapshot
GPES: a preemptive execution system for GPGPU computing
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Analysis and Implementation of Global Preemptive Fixed-Priority Scheduling with Dynamic Cache Allocation
inferredcites →https://doi.org/10.1109/rtcsa.2012.59openalex-snapshot
Supporting Low-Latency CPS Using GPUs and Direct I/O Schemes
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RGEM: A Responsive GPGPU Execution Model for Runtime Engines
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GPUSync: A Framework for Real-Time GPU Management
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Run-Time Scheduling Framework for Event-Driven Applications on a GPU-Based Embedded System
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Kernelet: High-Throughput GPU Kernel Executions with Dynamic Slicing and Scheduling
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Dissecting GPU Memory Hierarchy Through Microbenchmarking
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Scheduling processing of real-time data streams on heterogeneous multi-GPU systems
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WCET Measurement-based and Extreme Value Theory Characterisation of CUDA Kernels
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Adaptive and transparent cache bypassing for GPUs
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Scheduling Tasks with Mixed Timing Constraints in GPU-Powered Real-Time Systems
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ImageNet classification with deep convolutional neural networks
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