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Small is beautiful: Techniques to minimise memory footprint - Steven Pigeon - CppCon 2019
When we code, we often assume that the computer has an infinite amount of
memory. This is, of course, /very/ false. It is false for embedded
programming, where memory is often limited to a few megabytes or even a few
kilobytes, but it is also false for the most powerful workstations and
servers. Using memory wisely makes your application possible on small
systems as well as prevents, or at least reduces, scaling problems for
larger applications. While some programming languages are designed to hide
implementation details from the programmer, C++ allows the programmer to
specify, with a good level of control, how memory is allocated, structured,
and used. In this talk, we will explore what can be done at run-time with
negligible cost, what can be done at compile-time with meta-programming,
and how we can thwart default compiler behavior to achieve memory-efficient
type-safe data representations. We will also extend the discussion to the
higher-level reorganization of data structures in order to make a better
use of memory.
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Steven Pigeon
STEVEN PIGEON (steven.pigeon@uqar.ca) is an associate professor of mathematics and computer science in the Department of Mathematics, computer science, and engineering at the Université du Québec à Rimouski. He received his PhD. from the Université de Montréal for his thesis on data compression in 2001. His post-doctoral studies were conducted at Western Ontario then McMaster universities during 2002 and 2003. From 2003 to 2005, he developed laser-based 3D range finding equipment for industrial applications in the private sector. He returned to academia in 2006 where he joined an ÉTS research team on video adaptation and transcoding. In 2011-2012, he joined the Ubisoft industrial chair on artificial intelligence as principal systems architect. Since 2012, he teaches mathematics and computer science at the Université du Québec à Rimouski, where he also chairs the Mathematics and Computer Science section. His current research interests are, in addition to data compression, machine-efficient implementations of algorithms and memory-efficient data structures.
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