Profitability-based power allocation for speculative multithreaded systems

With the shrinking of transistors continuing to follow Moore´s Law and the non-scalability of conventional out-of-order processors, multi-core systems are becoming the design choice for industry. Performance extraction is thus largely alleviated from the hardware and placed on the pro-gr ammer/compiler camp, who now have to expose Thread Level Parallelism (TLP) to the underlying system in the form of explicitly parallel applications. Unfortunately, parallel programming is hard and error-prone. The programmer has to parallelize the work, perform the data placement, and deal with thread synchronization. Systems that support speculative multithreaded execution like Thread Level Speculation (TLS), offer an interesting alternative since they relieve the programmer from the burden of parallelizing applications and correctly synchronizing them. Since systems that support speculative multithreading usually treat all threads equally, they are energy-inefficient. This inefficiency stems from the fact that speculation occasionally fails and, thus, power is spent on threads that will have to be discarded. In this paper we propose a power allocation scheme for TLS systems, based on Dynamic Voltage and Frequency Scaling (DVFS), that tries to remedy this inefficiency. More specifically, we propose a profitability-based power allocation scheme, where we ??steal?? power fro m non-profitable threads and use it to speed up more useful ones. We evaluate our techniques for a state-of-the-art TLS system and show that, with minimal hardware support, they lead to improvements in ED of up to 39.6% with an average of 21.2%, for a subset of the SPEC 2000 Integer benchmark suite.