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Some Slides from:. Introduction to Sequential Circuits. U.C. Berkeley, Alan Mishchenko, Mike Miller, Gaetano Borriello. FSM (Finite State Machine) Optimization. State tables. identify and remove equivalent states. State minimization. assign unique binary code to each state.
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Some Slides from: Introduction to Sequential Circuits • U.C. Berkeley, • Alan Mishchenko, • Mike Miller, • Gaetano Borriello
FSM (Finite State Machine) Optimization State tables identify and remove equivalent states State minimization assign unique binary code to each state State assignment use unassigned state-codes as don’t care Combinational logic optimization net-list
Sequential Circuits • Sequential Circuits • Primitive sequential elements • Combinational logic • Models for representing sequential circuits • Finite-state machines (Moore and Mealy) • Representation of memory (states) • Changes in state (transitions) • Basic sequential circuits • Shift registers • Counters • Design procedure • State diagrams • State transition table • Next state functions
State Assignment • Choose bit vectors to assign to each “symbolic” state • With n state bits for m statesthere are 2n! / (2n – m)! state assignments [log n <= m <= 2n] • 2n codes possible for 1st state, 2n–1 for 2nd, 2n–2 for 3rd, … • Huge number even for small values of n and m • Intractable for state machines of any size • Heuristics are necessary for practical solutions • Optimize some metric for the combinational logic • Size (amount of logic and number of FFs) • Speed (depth of logic and fanout) • Dependencies (decomposition)
State Assignment Strategies • Possible Strategies • Sequential – just number states as they appear in the state table • Random – pick random codes • One-hot – use as many state bits as there are states (bit=1 –> state) • Output – use outputs to help encode states (counters) • Heuristic – rules of thumb that seem to work in most cases • No guarantee of optimality – an intractable problem
One-hot State Assignment • Simple • Easy to encode, debug • Small Logic Functions • Each state function requires only predecessor state bits as input • Good for Programmable Devices • Lots of flip-flops readily available • Simple functions with small support (signals its dependent upon) • Impractical for Large Machines • Too many states require too many flip-flops • Decompose FSMs into smaller pieces that can be one-hot encoded • Many Slight Variations to One-hot – “two hot”
Heuristics for State Assignment • Adjacent codes to states that share a common next state • Group 1's in next state map • Adjacent codes to states that share a common ancestor state • Group 1's in next state map • Adjacent codes to states that have a common output behavior • Group 1's in output map
General Approach to Heuristic State Assignment • All current methods are variants of this • 1) Determine which states “attract” each other (weighted pairs) • 2) Generate constraints on codes (which should be in same cube) • 3) Place codes on Boolean cube so as to maximize constraints satisfied (weighted sum) • Different weights make sense depending on whether we are optimizing for two-level or multi-level forms • Can't consider all possible embeddings of state clusters in Boolean cube • Heuristics for ordering embedding • To prune search for best embedding • Expand cube (more state bits) to satisfy more constraints
Output-Based Encoding • Reuse outputs as state bits - use outputs to help distinguish states • Why create new functions for state bits when output can serve as well • Fits in nicely with synchronous Mealy implementations
Inputs Present State Next State OutputsC TL TS ST H F0 – – HG HG 0 00 10 – 0 – HG HG 0 00 10 1 1 – HG HY 1 00 10 – – 0 HY HY 0 01 10 – – 1 HY FG 1 01 101 0 – FG FG 0 10 000 – – FG FY 1 10 00– 1 – FG FY 1 10 00– – 0 FY FY 0 10 01– – 1 FY HG 1 10 01 Example of KISS Format HG = ST’ H1’ H0’ F1 F0’ + ST H1 H0’ F1’ F0HY = ST H1’ H0’ F1 F0’ + ST’ H1’ H0 F1 F0’ FG = ST H1’ H0 F1 F0’ + ST’ H1 H0’ F1’ F0’ HY = ST H1 H0’ F1’ F0’ + ST’ H1 H0’ F1’ F0 Output patterns are unique to states, we do notneed ANY state bits – implement 5 functions(one for each output) instead of 7 (outputs plus2 state bits)
Current State Assignment Approaches • For tight encodings using close to the minimum number of state bits • Best of 10 random seems to be adequate (averages as well as heuristics) • Heuristic approaches are not even close to optimality • Used in custom chip design • One-hot encoding • Easy for small state machines • Generates small equations with easy to estimate complexity • Common in FPGAs and other programmable logic • Output-based encoding • Ad hoc - no tools • Most common approach taken by human designers • Yields very small circuits for most FSMs
State Assignment = Various Methods • Assign unique code to each state to produce logic-level description • utilize unassigned codes effectively as don’t cares • Choice for S state machine • minimum-bit encoding log S • maximum-bit encoding • one-hot encoding • using one bit per state • something in between • Modern techniques • hypercube embeddingof face constraint derived for collections of states (Kiss,Nova) • adjacency embeddingguided by weights derived between state pairs (Mustang)
Hypercube Embedding Technique • Observation : one -hot encoding is the easiest to decode Am I in state 2,5,12 or 17? binary : x4’x3’x2’x1x0’(00010) + x4’x3’x2x1’x0 (00101) + x4’x3x2x1’x0’(01100) + x4x3’x2’x1’x0 (10001) one hot : x2+x5+x12+x17 But one hot uses too many flip flops. • Exploit this observation 1. two-level minimization after one hot encoding identifies useful state group for decoding 2. assigning the states in each group to a single face of the hypercube allows a single product term to decode the group to states.
FSM Optimization 00 01 -0 S3 S2 0- 10 -1 11 01 -0 1- S4 S1 11 PI PO Combinational Logic v1 u1 NS PS v2 u2
State Group Identification Ex: state machine input current-state next state output 0 start S6 00 0 S2 S5 00 0 S3 S5 00 0 S4 S6 00 0 S5 start 10 0 S6 start 01 0 S7 S5 00 1 start S4 01 1 S2 S3 10 1 S3 S7 10 1 S4 S6 10 1 S5 S2 00 1 S6 S2 00 1 S7 S6 00 Symbolic Implicant : represent a transition from one or more state to a next state under some input condition.
Representation of Symbolic Implicant Symbolic cover representation is related to a multiple-valued logic. Positional cube notation : a p multiple-valued logic is represented as P bits (V1,V2,...,Vp) Ex:V = 4 for 5-value logic (00010) represent a set of values by one string V = 2 or V = 4 (01010)
Minimization of Multi-valued Logic Find a minimum multiple-valued-input cover - espresso Ex: A minimal multiple-valued-input cover 0 0110001 0000100 00 0 1001000 0000010 00 1 0001001 0000010 10
State Group Consider the first symbolic implicant 0 0110001 0000100 00 • This implicant shows that input “0” maps “state-2” or “state-3” or “state-7” into “state-5” and assert output “00” • This example shows the effect of symbolic logic minimization is to group together the states that are mapped by some input into the same next-stateand assert the same output. • We call it “state group” if we give encodings to the states in the state group in adjacent binary logic and no other states in the group face, then the states group can be implemented as a cube.
Group Face • group face : the minimal dimension subspace containing the encoding assigned to that group. Ex: 0010 0**0 group face 0100 0110
Hyper-cube Embedding c state groups : {2,5,12,17} {2,6,17} b a 12 17 6 5 2 2 17 wrong! 6 5 12
Hyper-cube Embedding c state groups : {2, 6, 17} {2, 4, 5} b a 6 17 2 5 4 17 6 2 4 wrong! 5
Hyper-cube Embedding • Advantage : • use two-level logic minimizer to identify good state group • almost all of the advantage of one-hot encoding,but fewer state-bit
Adjacency-Based State Assignment Basic algorithm: (1) Assign weight w(s,t) to each pair of states • weight reflects desire of placing states adjacent on the hypercube (2) Define cost function for assignment of codes to the states • penalize weights for the distance between the state codes eg. w(s,t) * distance(enc(s),enc(t)) (3) Find assignment of codes which minimize this cost functionsummed over all pairs of states. • heuristic to find an initial solution • pair-wise interchange (simulated annealing) to improve solution
Adjacency-Based State Assignment • Mustang : weight assignment technique based on loosely maximizing common cube factors
How to Assign Weight to State Pair • Assign weights to state pairs based on ability to extract a common-cube factor if these two states are adjacent on the hyper-cube.
Fan-Out-Oriented (examine present-state pairs) • Present state pair transition to the same next state S1 S3 S2 $$$ S1 S2 $$$$ $$$ S3 S2 $$$$ Add n to w(S1,S3) because of S2
Fan-Out-Oriented S3 S1 • present states pair asserts the same output $/j $/j S4 S2 $$$ S1 S2 $$$1$ $$$ S3 S4 $$$1$ Add 1 to w(S1 ,S3) because of output j
Fanin-Oriented (exam next state pair) • The same present state causes transition to next state pair. $$$ S1 S2 $$$$ $$$ S1 S4 $$$$ Add n/2 to w(S2,S4) because of S1 S1 S4 S2
Fanin-Oriented (exam next state pair) S1 S3 • The same input causes transition to next state pair. $0$ S1 S2 $$$$ $0$ S3 S4 $$$$ Add 1 to w(S2,S4) because of input i i i S2 S4
Which Method Is Better? • Which is better? • FSMs have no useful two-level face constraints => adjacency-embedding • FSMs have many two-level face constraints => face-embedding
Summary • Models for representing sequential circuits • Abstraction of sequential elements • Finite state machines and their state diagrams • Inputs/outputs • Mealy, Moore, and synchronous Mealy machines • Finite state machine design procedure • Deriving state diagram • Deriving state transition table • Determining next state and output functions • Implementing combinational logic • Implementation of sequential logic • State minimization • State assignment • Support in programmable logic devices
Some Tools History:Combinational Logic single FSM Hierarchy of FSM’s VIS (“handles” hierarchy) Facilities for managing networks of FSMs Sequential Circuit Optimization (single machine) MISII SIS Sequential Circuit Partitioning Facilities for handling latches