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MIT_IEP_Formal_Verification, 13th Dec Introduction To Formal Verification Subir K. Roy SDTC/SOC-COE Texas Instruments India Pvt. Ltd., Bangalore

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MIT_IEP_Formal_Verification, 13th Dec Organization of Presentation Motivation System on Chips and IPs Drawbacks of current verification methodology using simulation Why formal verification? Semantics/Models/Specification/Fairness Constraints Temporal Logics/Computational Tree Logic Binary Decision Diagrams

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MIT_IEP_Formal_Verification, 13th Dec Organization of Presentation Model Checking Verification Flow FV Related Issues – Intrinsic Limitations of FV Tool Important Verification Tasks Model Generation / Design Abstraction Compositional Verification using Assume- Guarantee

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MIT_IEP_Formal_Verification, 13th Dec Organization of Presentation IP Verification Issues Other Care Abouts Other Interesting Approaches Verification Hierarchy Conclusions

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MIT_IEP_Formal_Verification, 13th Dec Motivation Pentium SRT Division Bug : $0.5 billion loss to Intel Mercury Space Probe : Veered off course due to a failure to implement distance measurement in correct units. Ariane-5 Flight 501 failure : Internal sw exception during data conversion from 64 bit floating point to 16 bit signed integer value led to mission failure. Exception handling mechanism contributed to the processor being shutdown (This was part of the system specification).

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MIT_IEP_Formal_Verification, 13th Dec SoCs & IPs Typical SoCs consist of different components. CPU cores. Memory cores. DSP cores. Different peripherals & Interface buses. BIST and DFT Logic insertion. SoC realization turn around time (TAT) is rapidly increasing. TAT reduction through design re-use. Design Re-use : Employ IP blocks from IP vendors

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MIT_IEP_Formal_Verification, 13th Dec SoC Implementation Approaches Vendor Based Approach : ASIC Vendor/Design service group carries out implementation Partial Integration : System Designer implements proprietary & application specific logic. ASIC Vendor integrates above with their cores In house : ASIC Vendor designs specialized cores. System Designer implements proprietary & appli- cation specific logic, integrates cores & verifies integrated design

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MIT_IEP_Formal_Verification, 13th Dec Multiple Sources for IP Reuse Semiconductor houses I/O Pad, Processor Core, Custom Logic, Memory, Peripheral Interface, DFT/BIST Cores IP/Core Suppliers Processor Core, Peripheral Interface, Analog /Mixed Signal blocks (DAC, ADC, PLL) System Designer Controller, Custom Logic, AMS blocks

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MIT_IEP_Formal_Verification, 13th Dec Advantages of Core/IP based approach Short Time To Market (pre-designed) Less Expensive (reuse) Faster Performance (optimized algorithms and implementation) Lesser Area (optimized algorithms and implementation)

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MIT_IEP_Formal_Verification, 13th Dec “Where do bugs come from ?” Incorrect specifications. Misinterpretation of specifications. Misunderstanding between designers. Missed cases. Protocol non-conformance. Resource conflicts Cycle-level timing errors. ……

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MIT_IEP_Formal_Verification, 13th Dec Implications on Verification Abstraction of verification goals (Eg., Signals to Transactions, End to End Transactions) Rigorous verification of each individual SoC component seperately Extensive verification of full system Automation of all verification activities Reusability of verification components of unit Cores/IPs/VCs

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MIT_IEP_Formal_Verification, 13th Dec Drawbacks of Simulation Test bench creation – manual, error prone and time consuming. Simulation environment not re-usable. Large simulation regression run times: Hookup logic verification is done through long test sequences generated by controller. Simulation based verification can be incomplete. Design Errors : Related to asynchronous and concurrent interactions between components. Disadvantages : Exponential number of test vectors to exercise all possible transitions between components.

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MIT_IEP_Formal_Verification, 13th Dec Why Formal Verification? Formal Approaches : Model Checking Formal Model (Finite State Machine). Efficient Representation (Binary Decision Diagrams). Exhaustive Search (whenever possible). No test bench generation : Reduction in DV cycle time. Faster verification : Completion at fraction of time compared to simulation when no memory blow-up. Properties/Assertions when generic can be re-used and automatically generated. Comprehensive verification and coverage : High quality and confidence. Better ability to detect errors.

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MIT_IEP_Formal_Verification, 13th Dec Paradigm Framework Computational or Formal Logic Model Μ System Description: Formal Syntactic Representation Of Μ Deductive Proof Systems Formal Verification : Μ Ι= φ ?? Model Checking Algorithms Property Specification Language & Logic : Specification Formula φ General Mathematical Models Of System Mathematical Characterization Of System Behavior & Properties Logic Based Formal Methods

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MIT_IEP_Formal_Verification, 13th Dec Three-step process –Formal specification –Precise statement of properties –System requirements and environmental constraints –Logic - PL, FOL, temporal logic –Automata, labeled transition systems –Models –Flexible to model general to specific designs –Non-determinism, concurrency, fairness, –Transition systems, automata

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MIT_IEP_Formal_Verification, 13th Dec Three-step process (contd.) –Verification –Checking that model satisfies specification –Static and exhaustive checking –Automatic or semi-automatic

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MIT_IEP_Formal_Verification, 13th Dec Semantics of Finite State Systems Semantics associates behaviors –Branching Time semantics the tree of states obtained by unwinding the state machine graph possible choices are explicitly represented Linear Time Semantics the set of all possible `runs' in the system the set of all infinite paths in the state machine

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MIT_IEP_Formal_Verification, 13th Dec Non-determinism –This machine is nondeterministic in Idle state when req1 and req2 arrive. –Non-determinism due to abstraction –More than one behaviour for a given input IDLE M2 M1 rel2 rel1 req1 req2 req1

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MIT_IEP_Formal_Verification, 13th Dec Generating Formal Models –Pre-design activity –Automatic Translation from circuits/HDL designs –States decided by the latches/registers in the ckt. –Exponential blow-up in the size (State-explosion problem) –Usually abstractions required

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MIT_IEP_Formal_Verification, 13th Dec Formal Specifications –Verification involves checking that a design model meets its specification. –Specification states what the system is supposed to do –Design describes how this is done

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MIT_IEP_Formal_Verification, 13th Dec Formal Specifications Specification –Describes unambiguously and precisely the expected behavior of a design. –In general, a list of properties. –Includes environment constraints. –Symbolic logic or automata formalisms –Consistency and Completeness

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MIT_IEP_Formal_Verification, 13th Dec States, Labels, Transitions & Runs p,q s0 p,q s0 q,r s1 q,r s1 r s2 r r r r p,q s0 q,r s1 r s2

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MIT_IEP_Formal_Verification, 13th Dec Specification of Hardware blocks –Properties and Constraints specify possible states and transitions –They state set of possible valid `runs' –Valid runs are infinite sequences (or trees) of states and transitions –Formal specifications are finitistic and precise descriptions

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MIT_IEP_Formal_Verification, 13th Dec Specification of Hardware blocks Classification of Properties: –Safety properties “Undesirable states are never reached", “Desirable things always happen". –Progress or Liveness Properties “Desirable state repeatedly reached" “Desirable state eventually reached"

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MIT_IEP_Formal_Verification, 13th Dec Examples Safety Properties –A bus arbiter never grants the requests to two masters –Message received is the message sent –Elevator does not reach a floor unless it is requested Liveness Properties – Elevator attends to every request eventually – Every bus request is eventually granted – Every sent message was received

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MIT_IEP_Formal_Verification, 13th Dec Fairness Constraints –In general, not every run in a state machine is a valid behavior –Arbiter example the run in which master 2 is never granted the resource –But all runs are included in transition systems –Fairness constraints rule out certain runs Example –Every request eventually considered –The clock tick arrives infinitely often

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MIT_IEP_Formal_Verification, 13th Dec Properties of Hardware blocks –Temporal in nature –At any time only one units is accessing the bus –every request to access the bus is granted ultimately. –Two Kinds of TL –Linear Temporal Logic (LTL): Time is a linear sequence of events –Branching time temporal logic (CTL, CTL*): Time is a tree of events

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MIT_IEP_Formal_Verification, 13th Dec Syntax of CTL –Every atomic proposition is a CTL formula – If f and g are formulae then so are – f, (f g), (f g), (f g), (f g) –AG f - in all paths, in all state f (in all future, f) –EG f - in some path, in all states f –AF f - in all paths, in some state f (in every future f) –EF f - in some future f –A(f U g) - in all paths, f holds until g –E(f U g) - in some path, f holds until g –AX f - in every next state, f holds –EX f - in some next state f holds

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MIT_IEP_Formal_Verification, 13th Dec Examples AG ¬ (farm_go high_go_B) AGAF (farm_car AF(farm_go)) AG (mem_wr U mem_ack) EF (req 0 U grant 0 )

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MIT_IEP_Formal_Verification, 13th Dec EXAMPLE –Which of the following hold ? –AG p, EF!q, AX p, AG !q, EG !q, AX(p q) !p, !q p, !q !p, q

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MIT_IEP_Formal_Verification, 13th Dec CTL Verification Explicit Enumeration –Iterative labeling algorithm that labels all the states with sub formulae. –Start from the initial labels of atomic propositions –Iteratively add sub formulae as labels with each state based on the following equations: EF p = p EX p EX(EX p) EG p = p EX p EX(EX p) E (q U p) = p (q EX p) (q EX(q EX p))

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MIT_IEP_Formal_Verification, 13th Dec CTL Verification E[ !c2 U c1] n1 n2 s0 t1 c2 s7 n1 c2 s6 t1 t2 s8 t2 n1 s5 c1 t2 s4 t1 t2 s3 c1 n2 s2 t1 n2 s E[ !c2 U c1] n : non-critical section t : trying c : critical section Phase 1 : Label all states satisfying c1 with E[ !c2 U c1] Phase 2 : Label all states which do not satisfy c2 and have a successor state that is already labeled Phase 3 : Iterate Phase 2 until initial state is reached

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MIT_IEP_Formal_Verification, 13th Dec CTL Verification –Iteration terminates since states and subformulae are finite. –If initial states are labeled with the given formula then the model checking succeeds –If it fails, counterexample can be generated

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MIT_IEP_Formal_Verification, 13th Dec CTL Verification –Computation terminates –Computation involves backward breadth first traversal and calculation of Strongly Connected Subgraphs (cycles)

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MIT_IEP_Formal_Verification, 13th Dec Complexity of CTL model checking –Algorithm involves backward traversal –Linear on the sizes of both formulae and model –Size of the model exponential in size of latches –Reduction Techniques: –Symbolic Model checking Techniques –Compositional Verification –Symmetry based reduction

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MIT_IEP_Formal_Verification, 13th Dec ROBDDs –Example: –Properties –Unique representation of f for given variable ordering Checking f1 = f2: ROBDD isomorphism –Shared subgraphs: size reduction –Every path might not have all labels –Every non-leaf vertex has path(s) to 0 and 1 f = x 1.x 2 + x 3 ’ 1 0 x1x1 x2x2 x3x3 x1x1 x2x2 x3x3 x3x x3x3 x2x2

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MIT_IEP_Formal_Verification, 13th Dec Variable Ordering Problem f = x 1.x 2 + x 3.x 4 + x 5.x 6 Order 1,3,5,2,4,6 Order 1,2,3,4,5,6

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MIT_IEP_Formal_Verification, 13th Dec Operations on BDDs –Operators: Take ROBDD arguments, return ROBDD result. –Complexity polynomial in BDD size –BDD size limiting factor in most applications –Ongoing research on avoiding BDD blowup Variable ordering, Partitioned BDDs, Implicitly conjoined BDDs etc. –Quantification with BDDs – x 1. f(x 1, x 2, x 3 ) = f(0, x 2, x 3 ) + f(1, x 2, x 3 ) – x 1. f(x 1, x 2, x 3 ) = f(0, x 2, x 3 ). f(1, x 2, x 3 ) –Useful in Symbolic Model Checking

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MIT_IEP_Formal_Verification, 13th Dec Model Checking Sequential Circuits –Given: –A sequential circuit Finite state transition graph Flip-flops with next-state logic Transition relation between present and next states –A property in specialized logic –Prove that MODEL satisfies SPECIFICATION –In case of failure, counterexample desirable MODEL SPECIFICATION

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MIT_IEP_Formal_Verification, 13th Dec Example: 3-bit Counter x2x2 x1x1 x0x0 X0 X1 X2 Clk Model State transition graph defined by X0 = NOT( x 0) X1 = XOR( x 1, x 0) X2 = XOR( x 2, x 0. x 1) Property State x 0, x 1, x 2 = 111 is reached infinitely often starting from state 000

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MIT_IEP_Formal_Verification, 13th Dec CTL Properties AG AF ( x 1 x 2) x 1 or x 2 is satisfied infinitely often in the future 3-bit counter example: –“ The state x 0, x 1, x 2 = 111 is reached infinitely often starting from 000” –x 0 ’ x 1 ’ x 2 ’ AG AF ( x 0 x 1 x 2)

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MIT_IEP_Formal_Verification, 13th Dec Basic Approaches –Explicit state model checking –Requires explicit enumeration of states –Impractical for circuits with large state spaces –Useful tools exist: EMC, Murphi, SPIN, SMC … –Symbolic model checking –Represent transition relations and sets of states implicitly (symbolically) –BDDs used to manipulate implicit representations –Scales well to large state spaces (few 100 flip flops) –Fairly mature tools exist: SMV, VIS, FormalCheck...

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MIT_IEP_Formal_Verification, 13th Dec Model Checking –Reachability analysis –Find all states reachable from an initial set S0 of states –Check if a safety condition is violated in any reachable state –CTL property checking –Express property as formula in Computation Tree Logic (CTL) –Check if formula is satisfied by initial state in state transition graph

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MIT_IEP_Formal_Verification, 13th Dec Symbolic Model Checking –For 3-bit counter, set of states x 0, x 1, x 2 = {000, 010, 011, 001} can be represented by S ( x 0, x 1, x 2) = S( x ) = x 0 ’. BDD: –Set of state transitions can be represented by N ( x 0, x 1, x 2, X0, X1, X2) = N ( x, X) = (X0 x 0 ’ ) (X1 x 1 x 0) (X2 x 2 ( x 1. x 0)) 10 ox x0 1 0

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MIT_IEP_Formal_Verification, 13th Dec Forward Reachability –Start from set S0 of states –Set of states reachable in at most 1 step: S1 = S0 { X | x in S0 N( x, X) = 1} Expressed as Boolean functions: Given S0 ( x 0, x 1, x 2), S1 (X0, X1, X2) = S0 (X0, X1, X2) x 0, x 1, x 2. [S0 ( x 0, x 1, x 2) N( x 0, x 1, x 2, X0, X1, X2)] Given BDDs for S0 and N, BDD for S1 can be obtained S0 S1

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MIT_IEP_Formal_Verification, 13th Dec Forward Reachability –Compute S1 from S0, S2 from S1, S3 from S2, … –Predicate transformer F: S i+1 = F (S i ) –Continue until S k+1 = F (S k ) = S k –Least fixed point of F –S k = Set of all states reachable from S0 Computed symbolically -- using BDDs –Very large state sets can be represented compactly S0 Reachable states

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MIT_IEP_Formal_Verification, 13th Dec Backward Reachability –Give a set Z0 of states –Compute set of states from which some state in Z0 can be reached. –Analogous to forward reachability with minor modifications Z0

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MIT_IEP_Formal_Verification, 13th Dec Checking Safety Conditions –Safety condition must ALWAYS hold –E.g. Two bits in one-hot encoded state cannot be 1 –Z = set of states violating safety condition –Given S0 = set of initial states of circuit, –Compute R = set of all reachable states –Determine if Z intersects R, i.e. (Z R) 0 If YES, safety condition violated Satisfying assignment of (Z R): counterexample If NO, circuit satisfies safety condition –All computations in terms of BDDs

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MIT_IEP_Formal_Verification, 13th Dec Checking Safety Conditions –Start from Z = set of “bad” states –Find by backward reachability set of states B that can lead to a state in Z –Determine if S0 intersects B S0 R Z Z B Forward ReachabilityBackward Reachability

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MIT_IEP_Formal_Verification, 13th Dec Symbolic Model Checking –Given a model with set S0 of initial states and a CTL formula f –To determine if f is satisfied by all states in S0 –Convert f to g that uses only EX, EG, E[p U q] –CHECK(g) returns set of states satisfying g –If g = atomic proposition (e.g., x 1. x 2 + x 3), CHECK returns BDD for g –If g = EX p, EG p, E[p U q], CHECK uses reachability analysis to return BDD for set of states –Worst-case exponential complexity –Finally, determine if S0 CHECK(g)

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MIT_IEP_Formal_Verification, 13th Dec Model Checkers – State of the Art Symbolic model checkers can handle designs with 500 ~ 1000 flip flops For specific design domains, larger state spaces have been analyzed. Defining properties in CTL/LTL can be difficult and error prone Simpler property specification languages can help (E.g., PSL) Monitor based model checking.

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MIT_IEP_Formal_Verification, 13th Dec Queued Write Request Property of SCR Wrt_Decode Wrt_Arbiter Wrt_Cmd_Decode Master Slave 4 deep fifo where write_cmd_req is queued in 11 deep fifo to queue in the current owner of a processor as a slave.

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MIT_IEP_Formal_Verification, 13th Dec Queued Write Request Property Property on queuing of write requests from masters in a split bus transaction mode “When write command queue for a given master is empty, no write data transfers should originate from that master”. Abstraction for above property : Behavior related to property needed 3 out of a total of 72 submodules in SCR. 69 sub-modules were abstracted out. Property FSM : Assertions in OVL cannot capture this property. Separate Property FSM was coded.

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MIT_IEP_Formal_Verification, 13th Dec Assume-Guarantee Basic Idea P Q i1 + o2 o1 i2 PQ i1 o2 o1 i2 Global Property defined on o2 Decompose Assumption Guarantee Assumption P has to satisfy a local property on o1 which is treated as an assumption by Q to prove the global property on o2

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MIT_IEP_Formal_Verification, 13th Dec AOF Design Multiple Clock Processing (Root Module – AO_CLK) 16 bit Audio Data Processing (Root Module – AO_CH) Interrupt Request Processing (Root Module – AO_IRQ)

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MIT_IEP_Formal_Verification, 13th Dec Essential Module Interaction AO_CH_DMA AO_CH_SF AO_CK_DIV Global_CLK IO_CLK BCLKD LRCLKU LRCLKD GAT STANDBY UDR DREQDACK

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MIT_IEP_Formal_Verification, 13th Dec AOF Property Informal Statement for Property 1 When writing parallel data, converting them to serial ones, and outputting, the under-run error occurs if the next parallel data are not written. Precise Statement for Property 1 As long as DACK (Data Acknowledge) is received properly in response to DREQ (Data Requests), UDR (Data Starvation Signal) should never be asserted.

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MIT_IEP_Formal_Verification, 13th Dec Assume-Guarantee Approach Possible to use assume and guarantee in real designs. Individual module verification cheaper. Can fully exploit multiple clocks. Promising for SoC designs and designs based on IP re-use.

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MIT_IEP_Formal_Verification, 13th Dec Verification Flow Original HDL Description Design Abstraction Front-end Reduced HDL Description IFV IFV Script for Properties Verification Results Counter Example Logic Simulator Feedback For Design Error Correction Design Error No Design Error

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MIT_IEP_Formal_Verification, 13th Dec Problems in FV - Solutions Simulation can handle entire designs. State explosion in model checking limits designs that can be verified ( less than 500 ~ 1000 state bits). Solutions : Design Abstraction Reduced description (verification model) Fewer state bits ensures completion of state traversal process. In FV “Divided we solve, united we blowup” – Partition to contain state explosion (Compositional Verification).

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MIT_IEP_Formal_Verification, 13th Dec Important Verification Tasks Property Generation and Verification Model Generation Property Generation : Identifying and defining properties that the implementation model has to satisfy. Classification of Properties Safety Liveness Fairness

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MIT_IEP_Formal_Verification, 13th Dec Formal Verification Issues Major Efforts Reconstruct representations at various levels of abstraction. Data flow graphs. Data transfer graphs. State transition graphs of controllers. Module hierarchies. Block diagram of modules and sub-systems.

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MIT_IEP_Formal_Verification, 13th Dec Formal Verification Issues Reconstruction Reveals underlying interaction in modules. More abstracted information. Aids in defining properties. Evolve verification strategies for each design.

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MIT_IEP_Formal_Verification, 13th Dec Verification Model Generation Implementation Model Transformation For example, Multiple Clock Design Single Clock Design. Carried out before verification model generation. Design Abstraction Implementation Model typically has two behavioral components, Dataflow part and Control Part Dataflow Part : Generally easy to debug. Control Part : Dominating Source of Error. Design abstraction targets dataflow part – Remove as much as possible.

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MIT_IEP_Formal_Verification, 13th Dec Design Abstraction Removal or black boxing of module instances. Modification of module interface and module declaration. Partial removal of data flow behavior from some modules. Convert conditional assignments into fixed assignments. Reduce widths of some data registers and bit vector constants. Property related design abstraction. Conversion of multiple clock design into a single clock version. Automatic generation of properties.

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MIT_IEP_Formal_Verification, 13th Dec Areas Of Application For FV BIST and DFT Logic Controllers and Hookup Logic Buses and Bridges VLIW processors – new instructions and pipeline behavior Shared memory controller Floating point numeric coprocessor Power management unit

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MIT_IEP_Formal_Verification, 13th Dec Verification Issues Verification Time – 3 man months. Design Complexity – 700 state bits in the implementation model. Implementation model in Verilog RTL Familiarity – Low. Activity break up on 3 man months. 2 man months – To understand lowest level signals. 1 man month – For actual verification. Approach clearly not suitable for SoC designs. Concurrent design and verification efforts not possible in the above scenario.

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MIT_IEP_Formal_Verification, 13th Dec Other Care Abouts Bug hunting within IPs Bug hunting with IPs Coverage Issues What do the designers want? What do the functional verification engineers want? What can the formal verification engineers do about these wants? Where do they position themselves?

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MIT_IEP_Formal_Verification, 13th Dec Module Verification Issues Verification team develops deep understanding of implementation model. Design team codifies Functionality of each module and interaction between modules in a suitable and easily understandable format. Qualifies the defined set of properties as adequate.

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MIT_IEP_Formal_Verification, 13th Dec Other Interesting Approaches Bounded Model Checking Unbounded Model Checking Symbolic Simulation based Model Checking Generalized Symbolic Trajectory Evaluation based Model Checking Theorem Proving Formal Verification of Hybrid Systems (Mixed signal designs - discrete and continuous behavior).

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MIT_IEP_Formal_Verification, 13th Dec Verification Hierarchy Degree of Automation Coverage/ Expressive Power Simulation Equivalence Checking of structurally similar circuits Equivalence Checking Assume-Guarantee based symbolic simulation/Model Checking Temporal Logic Based Model Checking First-Order Theorem Proving Higher-Order Theorem Proving

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MIT_IEP_Formal_Verification, 13th Dec Conclusions Verification and design needs to be done concurrently. Need to influence implementation choices towards easing the formal verification process. Need to capture formally design information at various levels of abstraction. FV can prove properties which are difficult for simulation.

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