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What and Who
Title:Towards an Approximating Compiler for Numerical Computations
Speaker:Eva Darulova
coming from:Max Planck Institute for Software Systems
Speakers Bio:
Event Type:Joint Lecture Series
Visibility:D1, D2, D3, D4, D5, SWS, RG1, MMCI
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Level:Public Audience
Date, Time and Location
Date:Wednesday, 7 June 2017
Duration:60 Minutes
Building:E1 5
Computing resources are fundamentally limited and sometimes an exact solution
may not even exist. Thus, when implementing real-world systems, approximations
are inevitable, as are the errors introduced by them. The magnitude of errors is
problem-dependent but higher accuracy generally comes at a cost in terms of
memory, energy or runtime, effectively creating an accuracy-efficiency tradeoff.
To take advantage of this tradeoff, we need to ensure that the computed results
are sufficiently accurate, otherwise we risk disastrously incorrect results or
system failures. Unfortunately, the current way of programming with
approximations is mostly manual, and consequently costly, error prone and often
produces suboptimal results.

In this talk I will present our vision and efforts so far towards an approximating
compiler for numerical computations. Such a compiler would take as input exact
high-level code with an accuracy specification and automatically synthesize
an approximated implementation which is as efficient as possible, but verifiably
computes accurate enough results.
Name(s):Jennifer Müller
EMail:--email address not disclosed on the web
Video Broadcast
Video Broadcast:NoTo Location:
Tags, Category, Keywords and additional notes
Attachments, File(s):
Jennifer Müller/MPI-INF, 02/21/2017 01:28 PM
Last modified:
Uwe Brahm/MPII/DE, 06/07/2017 07:01 AM
  • Jennifer Müller, 02/21/2017 01:29 PM -- Created document.