Department of Computer Science and Technology

Technical reports

Accelerating control-flow intensive code in spatial hardware

Ali Mustafa Zaidi

May 2015, 170 pages

This technical report is based on a dissertation submitted February 2014 by the author for the degree of Doctor of Philosophy to the University of Cambridge, St. Edmund’s College.


Designers are increasingly utilizing spatial (e.g. custom and reconfigurable) architectures to improve both efficiency and performance in increasingly heterogeneous systems-on-chip. Unfortunately, while such architectures can provide orders of magnitude better efficiency and performance on numeric applications, they exhibit poor performance when implementing sequential, control-flow intensive code. This thesis studies the problem of improving sequential code performance in spatial hardware without sacrificing its inherent efficiency advantage.

I propose (a) switching from a statically scheduled to a dynamically scheduled, dataflow execution model, and (b) utilizing a newly developed compiler intermediate representation (IR) designed to expose ILP in spatial hardware, even in the presence of complex control flow. I describe this new IR – the Value State Flow Graph (VSFG) – and how it statically exposes ILP from control-flow intensive code by enabling control-dependence analysis, execution along multiple flows of control, as well as aggressive control-flow speculation. I also present a High-Level Synthesis (HLS) toolchain, that compiles unmodified high-level language code to dataflow custom hardware, via the LLVM compiler infrastructure.

I show that for control-flow intensive code, VSFG-based custom hardware performance approaches, or even exceeds the performance of a complex superscalar processor, while consuming only 1/4x the energy of an efficient in-order processor, and 1/8x that of a complex out-of-order processor. I also present a discussion of compile-time optimizations that may be attempted to further improve both efficiency and performance for VSFG-based hardware, including using alias analysis to statically partition and parallelize memory operations.

This work demonstrates that it is possible to use custom and/or reconfigurable hardware in heterogeneous systems to improve the efficiency of frequently executed sequential code, without compromising performance relative to an energy inefficient out-of-order superscalar processor.

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BibTeX record

  author =	 {Zaidi, Ali Mustafa},
  title = 	 {{Accelerating control-flow intensive code in spatial
  year = 	 2015,
  month = 	 may,
  url = 	 {},
  institution =  {University of Cambridge, Computer Laboratory},
  number = 	 {UCAM-CL-TR-870}