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Cache Performance of FastAllocating Programs Marcelo J. R. Goncalves and Andrew W. Appel
 

Summary: Cache Performance of Fast­Allocating Programs
Marcelo J. R. Gonc›alves and Andrew W. Appel
Princeton University
Department of Computer Science
{mjrg,appel}@cs.princeton.edu
Abstract
We study the cache performance of a set of ML programs, com­
piled by the Standard ML of New Jersey compiler. We find that
more than half of the reads are for objects that have just been allo­
cated. We also consider the effects of varying software (garbage
collection frequency) and hardware (cache) parameters. Confirm­
ing results of related experiments, we found that ML programs
can have good cache performance when there is no penalty for
allocation. Even on caches that have an allocation penalty, we
found that ML programs can have lower miss ratios than the C
and Fortran SPEC92 benchmarks.
Topics: 4 benchmarks, performance analysis; 21 hardware
design, measurements; 17 garbage collection, storage allocation;
46 runtime systems.
1 Introduction

  

Source: Appel, Andrew W. - Department of Computer Science, Princeton University

 

Collections: Computer Technologies and Information Sciences