DRACON: A Dedicated Hardware Infrastructure for Scalable Run-Time Management on Many-Core Systems

被引:5
|
作者
Gregorek, Daniel [1 ]
Rust, Jochen [1 ]
Garcia-Ortiz, Alberto [1 ]
机构
[1] Univ Bremen, Inst Electrodynam & Microelect, D-28359 Bremen, Germany
关键词
Computer architecture; many-core; dynamic run-time management; dedicated hardware; SUPPORT; MEDIA; SOC;
D O I
10.1109/ACCESS.2019.2937730
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Many-core architectures integrate a large number of comparatively small processing cores into a single chip. However, the high degree of parallelism increases the run-time resource management complexity and overhead. The employment of dedicated hardware enhancements potentially enables a high quality of the resource management while management overhead is mitigated. To exploit the potential of hardware enhancements, we propose a dedicated infrastructure for run-time resource management on homogeneous MIMD many-core processors. For hardware enhanced resource management, a scalable and cluster-based system architecture is implemented. The resulting architecture (DRACON) utilizes message passing based communication, the dedicated infrastructure and hardware accelerators for resource management. Acomprehensive evaluation for DRACON and reference architectures is performed using a transaction level simulation framework and dynamic task management as a use case. As benchmarks, synthetic models and task graph models of real-world applications are applied. The results reveal the limited scalability of classical architectures for resource management on many-cores. It is therefore necessary to apply cluster-based or moderately distributed architectures for many-core resource management. Further, the results demonstrate a significant performance improvement for the DRACON architecture at a number of hundreds of processing cores. Our evaluations show that DRACON generally outperforms software-only run-time management on many-core and achieves a performance improvement of up to 15.21% for single-program and more than 6% for mixed workloads.
引用
收藏
页码:121931 / 121948
页数:18
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