Fri 30 Oct 2015 11:37 - 12:00 at Grand Station 2 - 10. Empirical Studies & Approximation Chair(s): John Field

We present Topaz, a new task-based language for computations that execute on approximate computing platforms that may occasionally produce arbitrarily inaccurate results. Topaz maps tasks onto the approximate hardware and integrates the generated results into the main computation. To prevent unacceptably inaccurate task results from corrupting the main computation, Topaz deploys a novel outlier detection mechanism that recognizes and precisely reexecutes outlier tasks. Outlier detection enables Topaz to work effectively with approximate hardware platforms that have complex fault characteristics, including platforms with bit pattern dependent faults (in which the presence of faults may depend on values stored in adjacent memory cells). Our experimental results show that, for our set of benchmark applications, outlier detection enables Topaz to deliver acceptably accurate results (less than 1% error) on our target approximate hardware platforms. Depending on the application and the hardware platform, the overall energy savings range from 5 to 13 percent. Without outlier detection, only one of the applications produces acceptably accurate results.

Fri 30 Oct

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10:30 - 12:00
10. Empirical Studies & ApproximationOOPSLA at Grand Station 2
Chair(s): John Field Google
10:30
22m
Talk
Using C Language Extensions for Developing Embedded Software: A Case Study
OOPSLA
Markus Völter itemis, Germany, Arie van Deursen Delft University of Technology, Netherlands, Bernd Kolb itemis AG, Stephan Eberle itemis AG
DOI Pre-print Media Attached
10:52
22m
Talk
How Scale Affects Structure in Java ProgramsOOPSLA Artifact
OOPSLA
Crista Lopes University of California, Irvine, Joel Ossher University of California, Irvine
DOI Pre-print Media Attached File Attached
11:15
22m
Talk
Use at Your Own Risk: The Java Unsafe API in the WildOOPSLA Artifact
OOPSLA
Luis Mastrangelo University of Lugano, Switzerland, Luca Ponzanelli University of Lugano, Switzerland, Andrea Mocci University of Lugano, Switzerland, Michele Lanza University of Lugano, Switzerland, Matthias Hauswirth University of Lugano, Switzerland, Nate Nystrom University of Lugano, Switzerland
DOI Media Attached
11:37
22m
Talk
Approximate Computation with Outlier Detection in TopazOOPSLA Artifact
OOPSLA
Sara Achour Massachusetts Institute of Technology, USA, Martin C. Rinard Massachusetts Institute of Technology, USA
DOI Media Attached