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Timing Optimization Andreas Kuehlmann

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1 Timing Optimization Andreas Kuehlmann
EECS 219B Spring 2003 Timing Optimization Andreas Kuehlmann

2 Restructuring for Timing Optimization
Outline: Definitions and problem statement Overview of techniques (motivated by adders) Tree height reduction (THR) Generalized bypass transform (GBX) Generalized select transform (GST) Partial collapsing

3 Timing Optimization Factors determining delay of circuit:
Underlying circuit technology Circuit type (e.g. domino, static CMOS, etc.) Gate type Gate size Logical structure of circuit Length of computation paths False paths Buffering Parasitics Wire loads Layout

4 Problem Statement Given: Initial circuit function description
Library of primitive functions Performance constraints (arrival/required times) Generate: an implementation of the circuit using the primitive functions, such that: performance constraints are met circuit area is minimized

5 Current Design Process
Behavioral description Behavior Optimization (scheduling) Logic and latches Partitioning (retiming) Logic equations Logic synthesis Technology independent Technology mapping Gate library Perf. Constraints Delay models Gate netlist Timing driven place and route Layout

6 Technology Mapping for Delay
Function tree Buffer tree

7 Overview of Solutions for Delay
Circuit re-structuring Rescheduling operations to reduce time of computation Implementation of function trees (technology mapping) Selection of gates from library Minimum delay (load independent model - Kukimoto) Minimize delay and area (Jongeneel, DAC’00) (combines Lehman-Watanabe and Kukimoto) Implementation of buffer trees Touati (LT-trees) Singh Resizing Constant delay synthesis

8 Circuit Restructuring
Approaches: Local: Mimic optimization techniques in adders Carry lookahead (THR tree height reduction) Conditional sum (GST transformation) Carry bypass (GBX transformation) Global: Reduce depth of entire circuit Partial collapsing Boolean simplification

9 Restructuring Methods
Performance measured by levels, sensitizable paths, technology dependent delays Level based optimizations: Tree height reduction (Singh ‘88) Partial collapsing and simplification (Touati ‘91) Generalized select transform (Berman ‘90) Sensitizable paths Generalized bypass transform (McGeer ‘91)

10 Tree-Height Reduction (THR)
Singh’88: 6 n’ Collapsed Critical region 5 n Critical region 5 5 Duplicated logic l m 1 m 1 1 1 4 k 1 2 4 k i j 3 i j 3 h h 2 2 a b c d e f g a b c d e f g

11 Tree-Height Reduction
4 New delay = 5 n’ 3 n’ Collapsed Critical region 5 5 2 Duplicated logic 1 m m 1 1 1 1 1 2 4 1 k 2 4 k i j i j 3 3 h h 2 2 a b c d e f g a b c d e f g

12 Generalized bypass transform (GBX)
McGeer’91: Make critical path false Speed up the circuit Bypass logic of critical path(s) fm=f fm+1 … fn=g fm =f fm+1 … fn=g g’ 1 Boolean difference dg __ df s-a-0 redundant

13 GBX and KMS transform GBX gives little area increase, BUT creates an untestable fault (on control input to multiplexer) KMS transform: (remove false paths without increasing delay) fk is last node on false path that fans out. Duplicate false path {f1,…, fk} -> {f’1, … , f’k} f’j fans out to every fanout of fj except fj+1, and fj just fans out to fj+1 Set f0 input to f1 to controlling value and propagate constant (can do because path is false and does not fanout) KMS results Function of every node, except f1, … ,fk is unchanged Added k nodes Area added in linear in size of length of false paths; in practice small area increase.

14 KMS Keutzer, Malik, Saldanha’90: fm+1 fm+2 fm+k fm+k+1 … fn
Delay is not increased f’m+1 f’m+2 … f’m+k fm+1 fm+k+1 fm+2 fm+k … fn

15 Generalized select transform (GST)
Berman’90: Late signal feeds multiplexor a out b c d e f g a=0 b out c d e f g a=1 1 b a c d e f g

16 GST vs GBX a c g … h g’ b 1 a GBX dh __ da a c g GBX … h g’ b 1 a a=0
h g’ b 1 a GBX dh __ da a c g GBX … h g’ b 1 a a=0 b c d e f g a=1 b c d e f g a=0 out b GST c d e f g 1 a=1 b c d e f g a

17 GST vs GBX Select transform appears to be more area efficient
But Boolean difference generally more efficiently formed in practice No delay/speedup advantage for either transform Can reuse parts of the critical paths for multiple fanouts on GST GST out2 1 a a=0 out1 b c d e f g 1 a=1 b c d e f g a

18 Technology Independent Delay Reductions
Generally THR, GBX, GST (critical path based methods) work OK, but very greedy and computationally expensive Why are technology independent delay reductions hard? Lack of fast and accurate delay models # levels, fast but crude # levels + correction term (fanout, wires,… ): a little better, but still crude (what coefficients to use?) Technology mapped: reasonable, but very slow Place and route: better but extremely slow Silicon: best, but infeasibly slow (except for FPGAs) b e t r s l o w e r

19 Conclusions Variety of methods for delay optimization
No single technique dominates When applied to ripple-carry adder get Carry-lookahead adder (THR) Carry-bypass adder (GBX) Carry-select adder (GST) Clustering/Partial collapse All techniques ignore false paths when assessing the delay and critical regions Can use KMS transform to eliminate false paths without increasing delay (area increase however).

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