An SMT Based Method for Optimizing Arithmetic Computations in Embedded Software Code. Presented by: Kuldeep S. Meel Adapted from slides by Hassan Eldib and Chao Wang (Virginia Tech). A Robotic Dream. Having a tool that automatically synthesizes the optimum version of a software program.
Presented by: Kuldeep S. Meel
Adapted from slides by Hassan Eldib and Chao Wang (Virginia Tech)
Cost: US $350 million
Representations for 8-bit fixed-point numbers
Range ∝ Bit-width
Resolution ∝ Bit-width
Range & resolution of the input variables:
A -1000 3000
B -1000 3000
Fig. General Equation AST.
B + ≡
Detecting Overflow Errors
The parent nodes
Some sibling nodes
Some child nodes
Computing Redundant LSBs
All benchmark examples are public-domain examples
(602%, 194%, 5%, 40%, 32%, 1515%, 0% , 103%)
Original program New program
If we reduce microcontroller’s bit-width, how much error will be introduced?