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UID:submissions.supercomputing.org_SC25_sess620_post209@linklings.com
SUMMARY:CIRE: LLVM Analysis for Floating-Point Rounding Error Affected by 
 Precision and Optimizations
DESCRIPTION:Cayden Lund, Tanmay Tirpankar, and Ganesh Gopalakrishnan (Univ
 ersity of Utah)\n\nNumerical programmers often adjust precision settings a
 nd compiler optimizations to maximize performance, but these changes can u
 npredictably affect floating-point rounding errors. We present CIRE, a too
 l that statically estimates tight bounds on floating-point rounding error 
 by analyzing LLVM code which reflects precision and optimization choices. 
 This enables simultaneous optimization of both error and performance. CIRE
  uses symbolic automatic differentiation with interval-based optimization 
 to calculate maximum error across input intervals of interest. Our finding
 s reveal that (1) optimizations sometimes improve both performance and acc
 uracy by reducing the number of operations; (2) results vary significantly
  between different source languages, such as C++ and Rust; and (3) error a
 nd performance depend heavily on which subexpressions are subject to lower
 -precision allocation. We evaluate various combinations of optimizations a
 nd precision across popular benchmarks, providing insights into factors af
 fecting numerical error and computational performance.\n\nTag: Research & 
 ACM SRC Posters\n\nRegistration Category: Technical Program Reg Pass\n\nSe
 ssion Chairs: Kento Sato (RIKEN Center for Computational Science (R-CCS));
  Anja Gerbes (Georg-August-Universität Göttingen); and Chris Schlipalius (
 Pawsey Supercomputing Research Centre; Commonwealth Scientific and Industr
 ial Research Organisation (CSIRO), Australia)\n\n
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