International Conference on
Support for Programming
Languages and Operating Systems (ASPLOS 2011)
Beach, California, March 5 ~ 11, 2011
Ideas and Perspectives
This special Session wants to restore the original vision of the ASPLOS
Wild and Crazy Sessions, which was to present innovative ideas that may lead to
influential projects. Ideas and Perspectives will follow the tradition
of Wild and Crazy sessions but will look for submissions in a more serious
tone. Prospective authors can examine examples of successful vision sessions
at other conferences, for example PLDI FIT and DAC Wild And Crazy
- Innovative ideas relevant (or partly relevant) to ASPLOS,
especially those that promise to be previews of future influential projects.
- New challenges and application areas for ASPLOS technologies.
- Reflections, predictions, and trend identification.
Format of the Session
- 6-8 short talks (around 10 minutes), with enough time for
follow-up questions to start a discussion.
- Some of the talks will be given by invited speakers.
- Proceedings? Accepted submissions will be posted, together with
slides, on a blog site.
What is solicited
- 2-page papers in 10pt single-spaced, in either one- or single-column,
- Questions about suitability of a topic? Email email@example.com.
- Submissions due: Jan 5, 2011, 8pm PST
- Notification of acceptance: Jan 15, 2011
- Please send
submissions by the deadline to firstname.lastname@example.org.
Include a complete list of authors, their affiliations and email address, and
identify the corresponding author for your submission.
Submissions of selected presentations:
The Human Processing Units
Computer-mediated human micro-labor markets allow human effort
to be treated as a programmatic function call. Rather than thinking of
"employees" when we design tasks, we can characterize these platforms as
Human Processing Units (HPU). This is a first class computational
platform, which is different from CPU based computation, and deserves
careful characterization and study. We demonstrate that simple HPU
computation can be more accurate than complex CPU based algorithms on
some important computer vision tasks. We also argue that HPU computation
can be cheaper than state-of-the-art CPU based computation. Finally we
give some simplistic examples of characterizing the HPU.