Paper Info
Title
Towards Scheduling Hard Real-Time Image Processing Tasks On A Single Gpu
Abstract
Graphics Processing Units (GPU) are becoming the key hardware accelerators in the emerging image processing applications such as self-driving cars and mobile augmented reality systems. As GPUs execute launched workloads non-preemptively, their usage in safety-critical systems with hard real-time constraints is impeded. The existing solutions for scheduling real-time tasks on a single GPU focus on soft real-time systems. In this paper, we consider real-time systems with a single dedicated GPU handling sporadic tasks with hard deadlines and propose a scheduling approach based on time division multiplexing called the GPU-TDMh - a lightweight middleware framework located between the application and the GPU driver layers. We evaluate the proposed approach on a matrix multiplication benchmark on a heterogeneous platform. The experiments demonstrate the effectiveness of our method as well as superiority over the non-preemptive online scheduling policies.
Year
Venue
Keywords
2017
2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
Graphics Processing Units, Parallel Processing, Real-time, Scheduling, Time Division Multiplexing
Field
DocType
ISSN
Middleware,Kernel (linear algebra),Graphics,Computer vision,Scheduling (computing),Computer science,Server,Image processing,Artificial intelligence,Time-division multiplexing,Matrix multiplication,Embedded system
Conference
1522-4880
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Vladislav Golyanik12212.55
Mitra Nasri26710.09
Didier Stricker31266138.03