Application-Arrival Rate Aware Distributed Run-Time Resource Management for Many-Core Computing Platforms

Abstract

Modern many-core computing platforms execute a diverse set of dynamic workloads in the presence of varying application arrival rates. This inflicts strict requirements on run-time management to efficiently allocate system resources. On the way towards kilo-core processor architectures, centralized resource management approaches will most probably form a severe performance bottleneck, thus focus has been turned to the study of Distributed Run-Time Resource Management (DRTRM) schemes. In this article, we examine the behavior of a DRTRM of dynamic applications with malleable characteristics against stressing incoming application interval rate scenarios, using Intel SCC as the target many-core system. We show that resource allocation is highly affected by application input rate and propose an application-arrival aware DRTRM framework implementing an effective admission control strategy by carefully utilizing voltage and frequency scaling on parts of its resource allocation infrastructure. Through extensive experimental evaluation, we quantitatively analyze the behavior of the introduced DRTRM scheme and show that it achieves up to 44 percent performance gains while consuming 31 percent less energy, in comparison to a state-of-art DRTRM solution. In comparison to a centralized RTRM, the respective metric values rise up to 62 and 45 percent performance and energy gains, respectively.