Exploring Space-Time Trade-Off in Backtraces

Jean-Baptiste Besnard (), Julien Adam (), Allen D. Malony (), Sameer Shende (), Julien Jaeger (), Patrick Carribault () and Marc Pérache ()
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Jean-Baptiste Besnard: ParaTools SAS
Julien Adam: ParaTools SAS
Allen D. Malony: ParaTools Inc
Sameer Shende: ParaTools Inc
Julien Jaeger: CEA
Patrick Carribault: CEA
Marc Pérache: CEA

A chapter in Tools for High Performance Computing 2018 / 2019, 2021, pp 151-168 from Springer

Abstract: Abstract The backtrace is one of the most common operations done by profiling and debugging tools. It consists in determining the nesting of functions leading to the current execution state. Frameworks and standard libraries provide facilities enabling this operation, however, it generally incurs both computational and memory costs. Indeed, walking the stack up and then possibly resolving functions pointers (to function names) before storing them can lead to non-negligible costs. In this paper, we propose to explore a means of extracting optimized backtraces with an O(1) storage size by defining the notion of stack tags. We define a new data-structure that we called a hashed-trie used to encode stack traces at runtime through chained hashing. Our process called stack-tagging is implemented in a GCC plugin, enabling its use of C and C++ application. A library enabling the decoding of stack locators though both static and brute-force analysis is also presented. This work introduces a new manner of capturing execution state which greatly simplifies both extraction and storage which are important issues in parallel profiling.

Date: 2021
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DOI: 10.1007/978-3-030-66057-4_8

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