Description
Coarse-grained Reconfigurable Arrays (CGRAs) are promising accelerators capable

of accelerating even non-parallel loops and loops with low trip-counts. One challenge

in compiling for CGRAs is to manage both recurring and nonrecurring variables in

the register file (RF) of the CGRA. Although prior works

Coarse-grained Reconfigurable Arrays (CGRAs) are promising accelerators capable

of accelerating even non-parallel loops and loops with low trip-counts. One challenge

in compiling for CGRAs is to manage both recurring and nonrecurring variables in

the register file (RF) of the CGRA. Although prior works have managed recurring

variables via rotating RF, they access the nonrecurring variables through either a

global RF or from a constant memory. The former does not scale well, and the latter

degrades the mapping quality. This work proposes a hardware-software codesign

approach in order to manage all the variables in a local nonrotating RF. Hardware

provides modulo addition based indexing mechanism to enable correct addressing

of recurring variables in a nonrotating RF. The compiler determines the number of

registers required for each recurring variable and configures the boundary between the

registers used for recurring and nonrecurring variables. The compiler also pre-loads

the read-only variables and constants into the local registers in the prologue of the

schedule. Synthesis and place-and-route results of the previous and the proposed RF

design show that proposed solution achieves 17% better cycle time. Experiments of

mapping several important and performance-critical loops collected from MiBench

show proposed approach improves performance (through better mapping) by 18%,

compared to using constant memory.
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    Title
    • Scalable register file architecture for CGRA accelerators
    Contributors
    Date Created
    2016
    Resource Type
  • Text
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    Note
    • thesis
      Partial requirement for: M.S., Arizona State University, 2016
    • bibliography
      Includes bibliographical references (pages 28-30)
    • Field of study: Computer science

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    by Shail Dave

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