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Compiler for Fast, Accurate Mathematical Computing on Integer Processors

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNX07CA72P
Agency Tracking Number: 066364
Amount: $99,571.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: S7.02
Solicitation Number: N/A
Timeline
Solicitation Year: 2006
Award Year: 2007
Award Start Date (Proposal Award Date): 2007-01-19
Award End Date (Contract End Date): 2007-07-23
Small Business Information
1625 Shetland Ct.
Moscow, ID 83843-2480
United States
DUNS: 780523085
HUBZone Owned: Yes
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 David Buehler
 Principal Investigator
 (208) 902-1328
 david@entempocorp.com
Business Contact
 Gregory Donohoe
Title: President
Phone: (208) 883-3898
Email: gregd@entempocorp.com
Research Institution
N/A
Abstract

The proposers will develop a computer language compiler to enable inexpensive, low-power, integer-only processors to carry our mathematically-intensive comptutations at high speed, with excellent computational accuracy. This will enable space systems designers to select from a wide range of radiation-hard processors for math-intensive command and data handling applications such as spacecraft attitude control, advanced sensing, instrument data processing and calibration, and autonomous operation.

Integer-only processors are capable of accurate math-intensive computing if properly programmed using a fixed point computational model. This presents a major challenge to the program designer. Software tools are available to help the programmer analyze fixed point implementations, but not to create them. This kind of trial-and-error design cycle can be expensive, time-consuming and error-prone.

Our compiler will analyze system specifications, such as input data ranges and formats, architectural constraints, and a description of the computational algorithm. It will insert data scaling operations into the integer instruction stream to make the most effective use of the internal data representation. The resulting code will be an order of magnitude faster and more compact than a software floating point implementation, with very competitive computational accuracy.

This technology will be available for NASA programs immediately after Phase 2.

* Information listed above is at the time of submission. *

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