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» Parallelizing Functional Programs by Generalization
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IPL
2008
102views more  IPL 2008»
15 years 2 months ago
The connection between two ways of reasoning about partial functions
Undefined terms involving the application of partial functions and operators are common in program specifications and in discharging proof obligations that arise in design. One wa...
John S. Fitzgerald, Cliff B. Jones
105
Voted
DAC
2002
ACM
16 years 3 months ago
Hole analysis for functional coverage data
One of the main goals of coverage tools is to provide the user with informative presentation of coverage information. Specifically, information on large, cohesive sets of uncovere...
Oded Lachish, Eitan Marcus, Shmuel Ur, Avi Ziv
111
Voted
CASES
2005
ACM
15 years 4 months ago
Automating custom-precision function evaluation for embedded processors
Due to resource and power constraints, embedded processors often cannot afford dedicated floating-point units. For instance, the IBM PowerPC processor embedded in Xilinx Virtex-...
Ray C. C. Cheung, Dong-U Lee, Oskar Mencer, Wayne ...
211
Voted
POPL
2007
ACM
16 years 2 months ago
SAC: off-the-shelf support for data-parallelism on multicores
The advent of multicore processors has raised new demand for harnessing concurrency in the software mass market. We summarise our previous work on the data parallel, functional ar...
Clemens Grelck, Sven-Bodo Scholz
122
Voted
FOCS
1992
IEEE
15 years 6 months ago
Maximizing Non-Linear Concave Functions in Fixed Dimension
Consider a convex set P in IRd and a piecewise polynomial concave function F: P IR. Let A be an algorithm that given a point x IRd computes F(x) if x P, or returns a concave po...
Sivan Toledo