from pyabc import * import pyabc_split import par import redirect import sys import os import time import math global G_C,G_T,latches_before_abs,latches_before_pba,n_pos_before,x_factor """ The functions that are currently available from module _abc are: int n_ands(); int n_pis(); int n_pos(); int n_latches(); int n_bmc_frames(); int prob_status(); 1 = unsat, 0 = sat, -1 = unsolved int run_command(char* cmd); bool has_comb_model(); bool has_seq_model(); bool is_true_cex(); bool is_valid_cex(); return 1 if the number of PIs in the current network and in the current counter-example are equal int n_cex_pis(); return the number of PIs in the current counter-example int n_cex_regs(); return the number of flops in the current counter-example int cex_po(); returns the zero-based output PO number that is SAT by cex int cex_frame(); return the zero-based frame number where the outputs is SAT The last four APIs return -1, if the counter-example is not defined. """ #global variables stackno_gabs = stackno_gore = stackno_greg= 0 STATUS_UNKNOWN = -1 STATUS_SAT = 0 STATUS_UNSAT = 1 RESULT = ('SAT' , 'SAT', 'UNSAT', 'UNDECIDED', 'UNDECIDED,', 'UNDCIDED' ) Sat_reg = 0 Sat_true = 1 Unsat = 2 Undecided_reduction = 3 Undecided_no_reduction = 4 Error = 5 Restart = 6 xfi = x_factor = 1 #set this to higher for larger problems or if you want to try harder during abstraction max_bmc = -1 last_time = 0 # Function definitions: # simple functions: ________________________________________________________________________ # set_globals, abc, q, x, has_any_model, is_sat, is_unsat, push, pop # ALIASES def p(): return prove() def ps(): print_circuit_stats() def n_real_inputs(): """This gives the number of 'real' inputs. This is determined by trimming away inputs that have no connection to the logic. This is done by the ABC alias 'trm', which changes the current circuit. In some applications we do not want to change the circuit, but just to know how may inputs would go away if we did this. So the current circuit is saved and then restored afterwards.""" abc('w %s_savetempreal.aig; logic; trim; st'%f_name) n = n_pis() abc('r %s_savetempreal.aig'%f_name) return n def long(t): if t<20: t = t else: t = 20+(t-20)/3 return max(10,t) def rif(): """Not used""" global f_name print 'Type in the name of the aig file to be read in' s = raw_input() if s[-5:] == '.blif': f_name = s[:-5] else: f_name = s s = s+'.blif' run_command(s) x('st;constr -i') print_circuit_stats() a = n_ands() f = max(1,30000/a) f = min (f,16) x('scorr -c -F %d'%f) x('fold') print_circuit_stats() x('w %s_c.aig'%f_name) def abc(cmd): abc_redirect_all(cmd) def abc_redirect( cmd, dst = redirect.null_file, src = sys.stdout ): """This is our main way of calling an ABC function. Redirect, means that we suppress any output from ABC""" with redirect.redirect( dst, src ): return run_command( cmd ) def abc_redirect_all( cmd ): """This is our main way of calling an ABC function. Redirect, means that we suppress any output from ABC, including error printouts""" with redirect.redirect( redirect.null_file, sys.stdout ): with redirect.redirect( redirect.null_file, sys.stderr ): return run_command( cmd ) def set_globals(): """This sets global parameters that are used to limit the resources used by all the operations bmc, interpolation BDDs, abstract etc. There is a global factor 'x_factor' that can control all of the various resource limiting parameters""" global G_C,G_T,x_factor nl=n_latches() na=n_ands() np = n_pis() #G_C = min(500000,(3*na+500*(nl+np))) G_C = x_factor * min(100000,(3*na+500*(nl+np))) #G_T = min(250,G_C/2000) G_T = x_factor * min(75,G_C/2000) G_T = max(1,G_T) #print('Global values: BMC conflicts = %d, Max time = %d sec.'%(G_C,G_T)) def a(): """this puts the system into direct abc input mode""" print "Entering ABC direct-input mode. Type q to quit ABC-mode" n = 0 while True: print ' abc %d> '%n, n = n+1 s = raw_input() if s == "q": break run_command(s) def set_fname(name): """ Another way to set an f_name, but currently this is not used""" global f_name s = name if s[-4:] == '.aig': f_name = s[:-4] else: f_name = s s = s+'.aig' #read in file run_command(s) #print_circuit_stats() def read_file_quiet(fname=None): """This is the main program used for reading in a new circuit. The global file name is stored (f_name) Sometimes we want to know the initial starting name. The file name can have the .aig extension left off and it will assume that the .aig extension is implied. This should not be used for .blif files. Any time we want to process a new circuit, we should use this since otherwise we would not have the correct f_name.""" global max_bmc, f_name, d_name, initial_f_name, x_factor, init_initial_f_name x_factor = 1 max_bmc = -1 if fname is None: print 'Type in the name of the aig file to be read in' s = raw_input() else: s = fname if s[-4:] == '.aig': f_name = s[:-4] else: f_name = s s = s+'.aig' run_command(s) initial_f_name = f_name init_initial_f_name = f_name def read_file(): read_file_quiet() print_circuit_stats() def rf(): read_file() def write_file(s): """this is the main method for writing the current circuit to an AIG file on disk. It manages the name of the file, by giving an extension (s). The file name 'f_name' keeps increasing as more extensions are written. A typical sequence is name, name_smp, name_smp_abs, name_smp_abs_spec, name_smp_abs_spec_final""" global f_name """Writes out the current file as an aig file using f_name appended with argument""" f_name = '%s_%s'%(f_name,s) ss = '%s.aig'%(f_name) print 'WRITING %s: '%ss, print_circuit_stats() abc('w '+ss) def wf(): """Not used""" print 'input type of file to be written' s = raw_input() write_file(s) def bmc_depth(): """ Finds the number of BMC frames that the latest operation has used. The operation could be BMC, reachability interpolation, abstract, speculate. max_bmc is continually increased. It reflects the maximum depth of any version of the circuit including g ones, for which it is known that there is not cex out to that depth.""" global max_bmc b = n_bmc_frames() max_bmc = max(b,max_bmc) return max_bmc def set_max_bmc(b): """ Keeps increasing max_bmc which is the maximum number of time frames for which the current circuit is known to be UNSAT for""" global max_bmc max_bmc = max(b,max_bmc) def print_circuit_stats(): """Stardard way of outputting statistice about the current circuit""" global max_bmc i = n_pis() o = n_pos() l = n_latches() a = n_ands() b = max(max_bmc,bmc_depth()) c = cex_frame() if b>= 0: if c>=0: print 'PIs = %d, POs = %d, FF = %d, ANDs = %d, max depth = %d, CEX depth = %d'%(i,o,l,a,b,c) else: print 'PIs = %d, POs = %d, FF = %d, ANDs = %d, max depth = %d'%(i,o,l,a,b) else: if c>=0: print 'PIs = %d, POs = %d, FF = %d, ANDs = %d, CEX depth = %d'%(i,o,l,a,c) else: print 'PIs = %d, POs = %d, FF = %d, ANDs = %d'%(i,o,l,a) def q(): exit() def x(s): """execute an ABC command""" print "RUNNING: ", s run_command(s) def has_any_model(): """ check if a satisfying assignment has been found""" res = has_comb_model() or has_seq_model() return res def is_unsat(): if prob_status() == 1: return True else: return False def is_sat(): if prob_status() == 0: return True else: return False def wc(file): """writes so that costraints are preserved explicitly""" abc('&get;&w %s'%file) def rc(file): """reads so that if constraints are explicit, it will preserve them""" abc('&r %s;&put'%file) def fast_int(n): """This is used to eliminate easy-to-prove outputs. Arg n is conflict limit to be used in the interpolation routine. Typically n = 1 or 10""" n_po = n_pos() abc('int -k -C %d'%n) print 'Reduced POs from %d to %d'%(n_po,n_pos()) def refine_with_cex(): """Refines the greg (which contains the original problem with the set of FF's that have been abstracted). This generates a new abstraction (gabs) and modifies the greg file to reflect which regs are in the current abstraction""" global f_name print 'CEX in frame %d for output %d'%(cex_frame(),cex_po()) abc('&r %s_greg.aig; &abs_refine; &w %s_greg.aig'%(f_name,f_name)) return def generate_abs(n): """generates an abstracted model (gabs) from the greg file. The gabs file is automatically generated in the & space by &abs_derive. We store it away using the f_name of the problem being solved at the moment. The f_name keeps changing with an extension given by the latest operation done - e.g. smp, abs, spec, final, group. """ global f_name #we have a cex and we use this generate a new gabs file abc('&r %s_greg.aig; &abs_derive; &put; w %s_gabs.aig'%(f_name,f_name)) # do we still need the gabs file if n == 1: print 'New abstraction: ', print_circuit_stats() return #more complex functions: ________________________________________________________ #, abstract, pba, speculate, final_verify, dprove3 def simplify(): """Our standard simplification of logic routine. What it does depende on the problem size. For large problems, we use the &methods which use a simple circuit based SAT solver. Also problem size dictates the level of k-step induction done in 'scorr' The stongest simplification is done if n_ands < 20000. Then it used the clause based solver and k-step induction where |k| depends on the problem size """ # set_globals() ## print 'simplify initial ', ## ps() #abc('w t.aig') n=n_ands() abc('scl') if n > 40000: abc('&get;&scl;&put') n = n_ands() if n < 100000: abc("&dc2;&put;dr;&get;&lcorr;&dc2;&put;dr;&get;&scorr;&fraig;&dc2;&put;dr") run_command('ps') print '.', n = n_ands() if n<60000: abc("&get;&scorr -F 2;&put;dc2rs") print '.', #ps() else: abc("dc2rs") print '.', #ps() n = n_ands() n = n_ands() if n <= 40000: print '.', #ps() if n > 30000: abc("dc2rs") print '.', ## else: ## abc("scorr -F 2;dc2rs") ## print '.', ## ps() n = max(1,n_ands()) #ps() if n < 30000: abc('scl;rw;dr;lcorr;rw;dr') m = int(min( 60000/n, 16)) #print 'm = %d'%m if m >= 1: j = 1 while j <= m: set_size() #print 'j - %d'%j #abc('scl;dr;dc2;scorr -C 5000 -F %d'%j) if j<8: abc('dc2') else: abc('dc2rs') abc('scorr -C 5000 -F %d'%j) if check_size(): break j = 2*j #ps() continue print '.', def iterate_simulation(latches_before): """Subroutine of 'abstract' which does the refinement of the abstracted model, using counterexamples found by simulation. Simulation is controlled by the amount of memory it might use. At first wide but shallow simulation is done, bollowed by successively more narrow but deeper simulation""" global x_factor, f_name ## print 'RUNNING simulation iteratively' f = 5 w = 255 for k in range(9): f = min(f *2, 3500) w = max(((w+1)/2)-1,1) print '.', abc('sim -m -F %d -W %d'%(f,w)) if not is_sat(): continue while True: refine_with_cex() if is_sat(): print 'cex failed to refine abstraction ' return Sat_true generate_abs(0) latches_after = n_latches() print 'Latches increased to %d'%latches_after if latches_after >= .99*latches_before: abc('r %s_savetempabs.aig'%f_name) print "No reduction!." return Undecided_no_reduction abc('sim -m -F %d -W %d'%(f,w)) if not is_sat(): break def simulate(): """Simulation is controlled by the amount of memory it might use. At first wide but shallow simulation is done, bollowed by successively more narrow but deeper simulation""" global x_factor, f_name ## print 'RUNNING simulation iteratively' f = 5 w = 255 for k in range(9): f = min(f *2, 3500) w = max(((w+1)/2)-1,1) print '.', abc('sim -m -F %d -W %d'%(f,w)) if is_sat(): print 'cex found in frame %d'%cex_frame() return 'SAT' return 'UNDECIDED' def iterate_abstraction_refinement(latches_before,NBF): """Subroutine of 'abstract' which does the refinement of the abstracted model, using counterexamples found by BMC or BDD reachability""" global x_factor, f_name if NBF == -1: F = 2000 else: F = 2*NBF print '\nIterating BMC/PDR' always_reach = 0 cexf = 0 reach_failed = 0 while True: #print 'Generating problem abstraction' generate_abs(1) set_globals() latches_after = n_latches() if latches_after >= .98*latches_before: ## print 'No reduction' ## abc('r &s_savetemp.aig'%f_name) break ri = n_real_inputs() # No. of inputs after trm nlri = n_latches()+ri #reach_allowed = ((nlri<150) or (((cexf>250))&(nlri<300))) reach_allowed = ((nlri<75) or (((cexf>250))&(nlri<300))) pdr_allowed = True bmc = False t = max(1,G_T) if not F == -1: F = int(1.5*max_bmc) if (((reach_allowed or pdr_allowed ) and not reach_failed)): #cmd = 'reach -B 200000 -F 3500 -T %f'%t #cmd = 'reachx -e %d -t %d'%(int(long(t)),max(10,int(t))) #cmd = 'reachx -t %d'%max(10,int(t)) cmd = '&get;,pdr -vt=%f'%t else: #cmd = 'bmc3 -C %d -T %f -F %d'%(G_C,t,F) bmc = True cmd = '&get;,bmc -vt=%f'%(t) #cmd = '&get;,pdr -vt=%f'%(t) print '\n***RUNNING %s'%cmd #run_command(cmd) last_bmc = max_bmc abc(cmd) if prob_status() == 1: #print 'Depth reached %d frames, '%n_bmc_frames() print 'UNSAT' return Unsat cexf = cex_frame() #print 'cex depth = %d'%cexf #set_max_bmc(cexf -1) if ((not is_sat()) ): reach_failed = 1 # if ever reach failed, then we should not try it again on more refined models if is_sat(): #print 'CEX in frame %d for output %d'%(cex_frame(),cex_po()) #set_max_bmc(cexf-1) refine_with_cex() # if cex can't refine, status is set to Sat_true if is_sat(): print 'cex did not refine. Implies true_sat' return Sat_true else: print "No CEX found in %d frames"%n_bmc_frames() set_max_bmc(n_bmc_frames()) if bmc: break elif max_bmc> 1.2*last_bmc: # if pdr increased significantly over abs, the assume OK break else: continue latches_after = n_latches() if latches_after >= .98*latches_before: abc('r %s_savetempabs.aig'%f_name) print "No reduction!" return Undecided_no_reduction else: print 'Latches reduced from %d to %d'%(latches_before, n_latches()) return Undecided_reduction def abstract(): """ abstracts using N Een's method 3 - cex/proof based abstraction. The result is further refined using simulation, BMC or BDD reachability""" global G_C, G_T, latches_before_abs, x_factor set_globals() latches_before_abs = n_latches() abc('w %s_savetempabs.aig'%f_name) print 'Start: ', print_circuit_stats() c = 1.5*G_C #t = max(1,1.25*G_T) t = 2*max(1,1.25*G_T) s = min(max(3,c/30000),10) # stability between 3 and 10 time = max(1,.01*G_T) abc('&get;,bmc -vt=%f'%time) print 'BMC went %d frames'%n_bmc_frames() set_max_bmc(bmc_depth()) f = max(2*max_bmc,20) b = min(max(10,max_bmc),200) cmd = '&get;,abs -bob=%d -stable=%d -timeout=%f -vt=%f -depth=%d'%(b,s,t,t,f) print ' Running %s'%cmd run_command(cmd) if is_sat(): print 'Found true counterexample in frame %d'%cex_frame() return Sat_true NBF = bmc_depth() print 'Abstraction good to %d frames'%n_bmc_frames() set_max_bmc(NBF) abc('&w %s_greg.aig; &abs_derive; &put; w %s_gabs.aig'%(f_name,f_name)) ## print 'First abstraction: ', ## print_circuit_stats() latches_after = n_latches() #if latches_before_abs == latches_after: if latches_after >= .98*latches_before_abs: abc('r %s_savetempabs.aig'%f_name) print "No reduction!" return Undecided_no_reduction # refinement loop if (n_ands() + n_latches() + n_pis()) < 15000: print '\n***Running simulation iteratively' for i in range(5): result = iterate_simulation(latches_before_abs) if result == Restart: return result if result == Sat_true: return result result = iterate_abstraction_refinement(latches_before_abs, NBF) #if the result is 'Restart' we return and the calling routine increase #x_factor to try one more time. return result def absv(n,v): """This is a version of 'abstract' which can control the methods used in Een's abstraction code (method = n) as well as whether we want to view the output of this (v = 1)""" global G_C, G_T, latches_before_abs, x_factor #input_x_factor() #x_factor = 3 set_globals() latches_before_abs = n_latches() print 'Start: ', print_circuit_stats() c = 1.5*G_C t = max(1,1.25*G_T) s = min(max(3,c/30000),10) # stability between 3 and 10 if max_bmc == -1: time = max(1,.01*G_T) #abc('bmc3 -C %d -T %f -F 165'%(.01*G_C, time)) abc('&get;,bmc -vt=%f'%time) set_max_bmc(bmc_depth()) f = min(250,1.5*max_bmc) f = max(20, f) f = 10*f b = x_factor*20 if not n == 0: b = 10 b = max(b,max_bmc+2) b = b*2**(x_factor-1) b = 2*b print 'Neen abstraction params: Method #%d, %d conflicts, %d stable, %f sec.'%(n,c/3,s,t) if v == 1: run_command('&get; &abs_newstart -v -B %f -A %d -C %d -S %d -V %f'%(b,n,c/3,s,t)) else: abc('&get; &abs_newstart -v -B %f -A %d -C %d -S %d -T %f'%(b,n,c/3,s,t)) set_max_bmc(n_bmc_frames()) print 'Abstraction good to %d'%n_bmc_frames() abc('&w %s_greg.aig; &abs_derive; &put; w %s_gabs.aig'%(f_name,f_name)) print 'Final abstraction: ', print_circuit_stats() latches_after = n_latches() if latches_after >= .98*latches_before_abs: print "No reduction!" return Undecided_no_reduction return Undecided_reduction def spec(): """Main speculative reduction routine. Finds candidate sequential equivalences and refines them by simulation, BMC, or reachability using any cex found. """ input_x_factor() global G_C,G_T,n_pos_before, x_factor, n_latches_before set_globals() n_pos_before = n_pos() n_latches_before = n_latches() set_globals() t = max(1,.5*G_T) r = max(1,int(t)) print '\n***Running &equiv2 with C = %d, T = %f sec., F = %d -S 1 -R %d'%(G_C,t,200,r) abc("&get; &equiv2 -C %d -F 200 -T %f -S 1 -R %d; &semi -F 50; &speci -F 20 -C 1000;&srm; r gsrm.aig; w %s_gsrm.aig; &w %s_gore.aig"%((G_C),t,r,f_name,f_name)) print 'Initial speculation: ', print_circuit_stats() print 'Speculation good to %d frames'%n_bmc_frames() return def speculate(): """Main speculative reduction routine. Finds candidate sequential equivalences and refines them by simulation, BMC, or reachability using any cex found. """ global G_C,G_T,n_pos_before, x_factor, n_latches_before set_globals() n_pos_before = n_pos() def refine_with_cex(): """Refines the gore file to reflect equivalences that go away because of cex""" global f_name print 'CEX in frame %d for output %d'%(cex_frame(),cex_po()) abc('&r %s_gore.aig; &resim -m; &w %s_gore.aig'%(f_name,f_name)) #abc('&r %s_gore.aig; &equiv2 -vx ; &w %s_gore.aig'%(f_name,f_name)) return def generate_srm(n): """generates a speculated reduced model (srm) from the gore file""" global f_name pos = n_pos() ab = n_ands() abc('&r %s_gore.aig; &srm ; r gsrm.aig; w %s_gsrm.aig'%(f_name,f_name)) #do we still need to write the gsrm file if n == 0: if ((pos == n_pos()) and (ab == n_ands())): print 'Failed to refine' return 'failed' if n == 1: print 'Spec. Red. Miter: ', print_circuit_stats() return 'OK' def run_simulation(n): f = 5 w = (256/n)-1 for k in range(9): f = min(f * 2, 3500) w = max(((w+1)/2)-1,1) print '.', #generate_srm(0) abc('sim -m -F %d -W %d'%(f,w)) if not is_sat(): continue if cex_po() < n_pos_before: print 'Sim found true cex: Output = %d, Frame = %d'%(cex_po(),cex_frame()) return Sat_true refine_with_cex() if n_pos_before == n_pos(): return Undecided_no_reduction while True: result = generate_srm(0) if result == 'failed': return Sat_true abc('sim -m -F %d -W %d'%(f,w)) if not is_sat(): break if cex_po() < n_pos_before: print 'Sim found true cex: Output = %d, Frame = %d'%(cex_po(),cex_frame()) return Sat_true refine_with_cex() if n_pos_before == n_pos(): return Undecided_no_reduction return Undecided_no_reduction n_pos_before = n_pos() n_latches_before = n_latches() set_globals() t = max(1,.5*G_T) r = max(1,int(t)) abc('write spec_temp.aig') print '\n***Running &equiv2 with C = %d, T = %f sec., F = %d -S 1 -R %d'%(G_C,t,200,r) ## abc("&get; &equiv2 -C %d -F 200 -T %f -S 1 -R %d; &semi -F 50; &speci -F 20 -C 1000;&srm; r gsrm.aig; w %s_gsrm.aig; &w %s_gore.aig"%((G_C),t,r,f_name,f_name)) abc("&get; &equiv2 -C %d -F 200 -T %f -S 1 -R %d; &semi -W 63 -S 5 -C 500 -F 500; &speci -F 200 -C 5000;&srm; r gsrm.aig; w %s_gsrm.aig; &w %s_gore.aig"%((G_C),t,r,f_name,f_name)) print 'Initial speculation: ', print_circuit_stats() #print 'Speculation good to %d frames'%n_bmc_frames() #simplify() if n_pos_before == n_pos(): print 'No new outputs. Quitting speculate' return Undecided_no_reduction # return result is unknown if is_sat(): #print '\nWARNING: if an abstraction was done, need to refine it further\n' return Sat_true if n_latches() > .98*n_latches_before: pre_simp() if n_latches() > .98*n_latches_before: print 'Quitting speculation - not enough gain' abc('r spec_temp.aig') return Undecided_no_reduction # not worth it k = n_ands() + n_latches() + n_pis() n = 0 if k < 15000: n = 1 elif k < 30000: n = 2 elif k < 60000: n = 4 elif k < 120000: n = 8 if n > 0: # simulation can run out of memory for too large designs, so be careful print '\n***RUNNING simulation iteratively' for i in range(5): result = run_simulation(n) if result == Sat_true: return result simp_sw = 1 int_sw = 1 reach_sw = 0 cexf = 0 reach_failed = 0 init = 1 run_command('write temptemp.aig') print '\nIterating BMC or BDD reachability' while True: # now try real hard to get the last cex. set_globals() if not init: set_size() result = generate_srm(1) if check_size() == True: print 'Failed to refine' return Error if result == 'failed': return Sat_true if simp_sw == 1: na = n_ands() simplify() if n_ands() > .7*na: #if not significant reduction, stop simplification simp_sw = 0 if n_latches() == 0: return check_sat() init = 0 # make it so that next time it is not the first time through time = max(1,G_T/(5*n_pos())) if int_sw ==1: npo = n_pos() if n_pos() > .5*npo: # if not sufficient reduction, turn this off int_sw = 0 if is_sat(): #if fast interpolation found a cex cexf = cex_frame() set_max_bmc(cexf - 1) if cex_po() < n_pos_before: print 'Int found true cex: Output = %d, Frame = %d'%(cex_po(),cex_frame()) return Sat_true refine_with_cex() if ((n_pos_before == n_pos()) or (n_latches_before == n_latches())): abc('r temp_spec.aig') return Undecided_no_reduction if is_sat(): print '1. cex failed to refine abstraction' return Sat_true continue else: if n_latches() == 0: return check_sat() ri = n_real_inputs() #seeing how many inputs would trm get rid of nlri = n_latches() + ri reach_allowed = ((nlri<75) or (((cexf>250)) and (nlri<300))) pdr_allowed = True bmc = False if (((reach_allowed or pdr_allowed ) and not reach_failed)): t = max(1,1.2*G_T) f = max(3500, 2*max_bmc) #cmd = 'reachx -t %d'%max(10,int(t)) cmd ='&get;,pdr -vt=%f'%t else: t = max(1,1.5*G_T) if max_bmc == -1: f = 200 else: f = max_bmc f = int(1.5*f) #cmd = 'bmc3 -C %d -T %f -F %f'%(1.5*G_C,1.2*t,f) bmc = True cmd = '&get;,bmc -vt=%f'%(1.2*t) print '\n***Running %s'%cmd last_bmc = max_bmc abc(cmd) #run_command(cmd) if is_sat(): cexf = cex_frame() #set_max_bmc(cexf - 1) #This is a temporary fix since reachx always reports cex_ps = 0 if ((cex_po() < n_pos_before) and (cmd[:4] == '&get')): print 'BMC/PDR found true cex: Output = %d, Frame = %d'%(cex_po(),cex_frame()) return Sat_true #End of temporary fix refine_with_cex()#change the number of equivalences if n_pos_before == n_pos(): return Undecided_no_reduction continue else: set_max_bmc(n_bmc_frames()) if prob_status() == 1: #print 'Convergence reached in %d frames'%n_bmc_frames() return Unsat print 'No cex found in %d frames'%n_bmc_frames() if bmc: break elif max_bmc > 1.2*last_bmc: break else: reach_failed = 1 init = 1 continue if n_pos_before == n_pos(): return Undecided_no_reduction else: return Undecided_reduction def set_size(): """Stores the problem size of the current design. Size is defined as (PIs, POs, ANDS, FF, max_bmc)""" global npi, npo, nands, nff, nmd npi = n_pis() npo = n_pos() nands = n_ands() nff = n_latches() nmd = max_bmc def check_size(): """Assumes the problem size has been set by set_size before some operation. This checks if the size was changed Size is defined as (PIs, POs, ANDS, FF, max_bmc) Returns TRUE is size is the same""" global npi, npo, nands, nff, nmd result = ((npi == n_pis()) and (npo == n_pos()) and (nands == n_ands()) and (nff == n_latches()) and (nmd == max_bmc)) ## if result == 1: ## print 'Size unchanged' return result def inferior_size(): """Assumes the problem size has been set by set_size beore some operation. This checks if the new size is inferior (larger) to the old one Size is defined as (PIs, POs, ANDS, FF)""" global npi, npo, nands, nff result = ((npi < n_pis()) or (npo < n_pos()) or (nands < n_ands()) ) return result def quick_verify(n): """Low resource version of final_verify n = 1 means to do an initial simplification first""" abc('trm') if n == 1: simplify() if n_latches == 0: return check_sat() abc('trm') if is_sat(): return Sat_true print 'After trimming: ', print_circuit_stats() #try_rpm() set_globals() t = max(1,.4*G_T) print ' Running PDR for %d sec '%(t) abc('&get;,pdr -vt=%f'%(t*.8)) status = get_status() if not status == Unsat: print 'PDR went to %d frames, '%n_bmc_frames(), print RESULT[status] return status #temporary if status <= Unsat: return status N = bmc_depth() c = max(G_C/10, 1000) t = max(1,.4*G_T) print ' RUNNING interpolation with %d conflicts, max %d sec and 100 frames'%(c,t) #abc('int -v -F 100 -C %d -T %f'%(c,t)) abc(',imc -vt=%f '%t) status = get_status() if status <= Unsat: print 'Interpolation went to %d frames, '%n_bmc_frames(), print RESULT[status] return status L = n_latches() I = n_real_inputs() if ( ((I+L<200)&(N>100)) or (I+L<125) or L < 51 ): #heuristic that if bmc went deep, then reachability might also t = max(1,.4*G_T) cmd = 'reachx -t %d'%max(10,int(t)) print ' Running %s'%cmd abc(cmd) status = get_status() if status <= Unsat: print 'Reachability went to %d frames, '%n_bmc_frames() print RESULT[status] return status print 'BDD reachability aborted' simplify() #why is this here if n_latches() == 0: print 'Simplified to 0 FF' return check_sat() set_max_bmc(bmc_depth()) # doesn't do anything print 'No success, max_depth = %d'%max_bmc return Undecided_reduction def get_status(): """this simply translates the problem status encoding done by ABC (-1,0,1)=(undecided,SAT,UNSAT) into the status code used by our python code.""" status = prob_status() #interrogates ABC for the current status of the problem. # 0 = SAT if status == 1: status = Unsat if status == -1: #undecided status = Undecided_no_reduction return status def try_rpm(): """rpm is a cheap way of doing reparameterization and is an abstraction method, so may introduce false cex's. It finds a minimum cut between the PIs and the main sequential logic and replaces this cut by free inputs. A quick BMC is then done, and if no cex is found, we assume the abstraction is valid. Otherwise we revert back to the original problem before rpm was tried.""" global x_factor if n_ands() > 30000: return set_globals() pis_before = n_pis() abc('w %s_savetemp.aig'%f_name) abc('rpm') result = 0 if n_pis() < .5*pis_before: bmc_before = bmc_depth() #print 'running quick bmc to see if rpm is OK' t = max(1,.1*G_T) #abc('bmc3 -C %d, -T %f'%(.1*G_C, t)) abc('&get;,bmc -vt=%f'%t) if is_sat(): #rpm made it sat by bmc test, so undo rpm abc('r %s_savetemp.aig'%f_name) else: abc('trm') print 'WARNING: rpm reduced PIs to %d. May make SAT.'%n_pis() result = 1 else: abc('r %s_savetemp.aig'%f_name) return result def final_verify(): """This is the final method for verifying anything is nothing else has worked. It first tries BDD reachability if the problem is small enough. If this aborts or if the problem is too large, then interpolation is called.""" global x_factor set_globals() ## simplify() ## if n_latches() == 0: ## return check_sat() ## abc('trm') #rpm_result = try_rpm() set_globals() N = bmc_depth() L = n_latches() I = n_real_inputs() #try_induction(G_C) c = max(G_C/5, 1000) t = max(1,G_T) print '\n***Running PDR for %d sec'%(t) abc('&get;,pdr -vt=%f'%(t*.8)) status = get_status() if status <= Unsat: print 'PDR went to %d frames, '%n_bmc_frames(), print RESULT[status] return status if ( ((I+L<250)&(N>100)) or (I+L<200) or (L<51) ): #heuristic that if bmc went deep, then reachability might also t = max(1,1.5*G_T) #cmd = 'reach -v -B 1000000 -F 10000 -T %f'%t #cmd = 'reachx -e %d'%int(long(t)) #cmd = 'reachx -e %d -t %d'%(int(long(t)),max(10,int(t))) cmd = 'reachx -t %d'%max(10,int(t)) print '\n***Running %s'%cmd abc(cmd) status = get_status() if status <= Unsat: print 'Reachability went to %d frames, '%n_bmc_frames(), print RESULT[status] return status print 'BDD reachability aborted' return status #temporary #f = max(100, bmc_depth()) print '\n***RUNNING interpolation with %d conflicts, %d sec, max 100 frames'%(c,t) #abc('int -v -F 100 -C %d -T %f'%(c,t)) abc(',imc -vt=%f '%t) status = get_status() if status <= Unsat: print 'Interpolation went to %d frames, '%n_bmc_frames(), print RESULT[status] return status t = max(1,G_T) simplify() if n_latches() == 0: return check_sat() print 'Undecided' return Undecided_reduction def check_sat(): """This is called if all the FF have disappeared, but there is still some logic left. In this case, the remaining logic may be UNSAT, which is usually the case, but this has to be proved. The ABC command 'dsat' is used fro combinational problems""" ## if n_ands() == 0: ## return Unsat abc('orpos;dsat -C %d'%G_C) if is_sat(): return Sat_true elif is_unsat(): return Unsat else: return Undecided_no_reduction def try_era(s): """era is explicit state enumeration that ABC has. It only works if the number of PIs is small, but there are cases where it works and nothing else does""" if n_pis() > 12: return cmd = '&get;&era -mv -S %d;&put'%s print 'Running %s'%cmd run_command(cmd) def try_induction(C): """Sometimes proving the property directly using induction works but not very often. For 'ind' to work, it must have only 1 output, so all outputs are or'ed together temporarily""" return Undecided_reduction print '\n***Running induction' abc('w %s_temp.aig'%f_name) abc('orpos; ind -uv -C %d -F 10'%C) abc('r %s_savetemp.aig'%f_name) status = prob_status() if not status == 1: return Undecided_reduction print 'Induction succeeded' return Unsat def final_verify_recur(K): """During prove we make backups as we go. These backups have increasing abstractions done, which can cause non-verification by allowing false counterexamples. If an abstraction fails with a cex, we can back up to the previous design before the last abstraction and try to proceed from there. K is the backup number we start with and this decreases as the backups fails. For each backup, we just try final_verify. If ever we back up to 0, which is the backup just after simplify, we then try speculate on this. This often works well if the problem is a SEC problem where there are a lot of equivalences across the two designs.""" for j in range(K): i = K-(j+1) if i == 0: #don't try final verify on original status = 3 break print '\nVerifying backup number %d:'%i, abc('r %s_backup_%d.aig'%(initial_f_name,i)) print_circuit_stats() status = final_verify() if status >= Unsat: return status if i > 0: print 'SAT returned, Running less abstract backup' continue break if ((i == 0) and (status > Unsat) and (n_ands() > 0)): print '\n***Running speculate on initial backup number %d:'%i, abc('r %s_backup_%d.aig'%(initial_f_name,i)) ps() if n_ands() < 20000: status = speculate() if ((status <= Unsat) or (status == Error)): return status status = final_verify() if status == Unsat: return status else: return Undecided_reduction def smp(): pre_simp() write_file('smp') def pre_simp(): """This uses a set of simplification algorithms which preprocesses a design. Includes forward retiming, quick simp, signal correspondence with constraints, trimming away PIs, and strong simplify""" ## print "Trying BMC for 2 sec." ## abc("&get; ,bmc -vt=2") ## if is_sat(): ## return Sat_true set_globals() if n_latches == 0: return check_sat() #print '\n*** Running forward' try_forward() #print \n*** Running quick simp' quick_simp() #print 'Running_scorr_constr' status = try_scorr_constr() #status = 3 #print 'Running trm' if ((n_ands() > 0) or (n_latches()>0)): abc('trm') print 'Forward, quick_simp, scorr_constr,: ', print_circuit_stats() if n_latches() == 0: return check_sat() status = process_status(status) if status <= Unsat: return status simplify() print 'Simplify: ', print_circuit_stats() #abc('w temp_simp.aig') if n_latches() == 0: return check_sat() try_phase() if n_latches() == 0: return check_sat() #abc('trm') if ((n_ands() > 0) or (n_latches()>0)): abc('trm') status = process_status(status) if status <= Unsat: return status status = try_scorr_constr() abc('trm') return process_status(status) def try_scorr_constr(): set_size() abc('w %s_savetemp.aig'%f_name) status = scorr_constr() if inferior_size(): abc('r %s_savetemp.aig'%f_name) return status def process(status): """Checks if there are no FF and if so checks if the remaining combinational problem is UNSAT""" if n_latches() == 0: return check_sat() return status def try_phase(): """Tries phase abstraction. ABC returns the maximum clock phase it found using n_phases. Then unnrolling is tried up to that phase and the unrolled model is quickly simplified (with retiming to see if there is a significant reduction. If not, then revert back to original""" n = n_phases() if ((n == 1) or (n_ands() > 40000)): return print 'Number of possible phases = %d'%n abc('w %s_savetemp.aig'%f_name) na = n_ands() nl = n_latches() ni = n_pis() no = n_pos() cost_init = (1*n_pis())+(2*n_latches())+1*n_ands() cost_min = cost_init cost = cost_init abc('w %s_best.aig'%f_name) for j in range(4): abc('r %s_savetemp.aig'%f_name) p = 2**(j+1) if p > n: break abc('phase -F %d'%p) if na == n_ands(): break abc('scl;rw') if n_latches() > nl: #why would this ever happen break #print_circuit_stats() abc('rw;lcorr;trm') #print_circuit_stats() cost = (1*n_pis())+(2*n_latches())+1*n_ands() if cost < cost_min: cost_min = cost abc('w %s_best.aig'%f_name) else: break if cost < cost_init: abc('r %s_best.aig'%f_name) simplify() abc('trm') print 'Phase abstraction obtained :', print_circuit_stats() return abc('r %s_savetemp.aig'%f_name) return def try_forward(): """Attempts most forward retiming, and latch correspondence there. If attempt fails to help simplify, then we revert back to the original design This can be effective for equivalence checking problems where synthesis used retiming""" abc('w %s_savetemp.aig'%f_name) if n_ands() < 30000: abc('dr') abc('lcorr') nl = n_latches() na = n_ands() abc('w %s_savetemp0.aig'%f_name) abc('r %s_savetemp.aig'%f_name) abc('dr -m') abc('lcorr') abc('dr') if ((n_latches() <= nl) and (n_ands() < na)): print 'Forward retiming reduced size to: ', print_circuit_stats() return else: abc('r %s_savetemp0.aig'%f_name) return return def quick_simp(): """A few quick ways to simplify a problem before more expensive methods are applied. Uses & commands if problem is large. These commands use the new circuit based SAT solver""" na = n_ands() if na < 30000: abc('scl;rw') elif na < 80000: abc('&get;&scl;&put;rw') def scorr_constr(): """Extracts implicit constraints and uses them in signal correspondence Constraints that are found are folded back when done""" na = max(1,n_ands()) if ((na > 40000) or n_pos()>1): return Undecided_no_reduction f = 40000/na f = min(f,16) n_pos_before = n_pos() f = 1 #temporary until bug fixed. abc('w %s_savetemp.aig'%f_name) if n_ands() < 3000: cmd = 'unfold -a -F 2' else: cmd = 'unfold' abc(cmd) if ((n_ands() > na) or (n_pos() == n_pos_before)): abc('r %s_savetemp.aig'%f_name) return Undecided_no_reduction print_circuit_stats() print 'Number of constraints = %d'%(n_pos() - n_pos_before) abc('scorr -c -F %d'%f) abc('fold') return Undecided_no_reduction def process_status(status): """ if there are no FF, the problem is combinational and we still have to check if UNSAT""" if n_latches() == 0: return check_sat() return status def input_x_factor(): """Sets the global x_factor according to user input""" global x_factor, xfi print 'Type in x_factor:', xfi = x_factor = input() print 'x_factor set to %f'%x_factor def prove(a): """Proves all the outputs together. If ever an abstraction was done then if SAT is returned, we make RESULT return "undecided". If a == 1 do not run speculate""" global x_factor,xfi,f_name x = time.clock() max_bmc = -1 K = 0 print 'Initial: ', print_circuit_stats() x_factor = xfi print 'x_factor = %f'%x_factor print '\n***Running pre_simp' set_globals() if n_latches() > 0: status = pre_simp() else: status = check_sat() if ((status <= Unsat) or (n_latches() == 0)): print 'Time for proof = %f sec.'%(time.clock() - x) return RESULT[status] if n_ands() == 0: #abc('bmc3 -T 2') abc('&get;,bmc -vt=2') if is_sat(): return 'SAT' abc('trm') write_file('smp') abc('w %s_backup_%d.aig'%(initial_f_name,K)) K = K +1 set_globals() ## if ((n_ands() < 30000) and (a == 1) and (n_latches() < 300)): if ((n_ands() < 30000) and (n_latches() < 300)): print '\n***Running quick_verify' status = quick_verify(0) if status <= Unsat: if not status == Unsat: print 'CEX in frame %d'%cex_frame() print 'Time for proof = %f sec.'%(time.clock() - x) return RESULT[status] if n_ands() == 0: #abc('bmc3 -T 2') abc('&get;,bmc -vt=2') if is_sat(): return 'SAT' print'\n***Running abstract' nl_b = n_latches() status = abstract() abc('trm') write_file('abs') status = process_status(status) if ((status <= Unsat) or status == Error): if status < Unsat: print 'CEX in frame %d'%cex_frame() ## status = final_verify_recur(K) ## write_file('final') print 'Time for proof = %f sec.'%(time.clock() - x) return RESULT[status] print 'Time for proof = %f sec.'%(time.clock() - x) return RESULT[status] abc('w %s_backup_%d.aig'%(initial_f_name,K)) K = K +1 if ((n_ands() > 20000) or (a == 1)): print 'Speculation skipped because either too large or already done' K = 2 elif n_ands() == 0: print 'Speculation skipped because no AND nodes' K = 2 else: print '\n***Running speculate' status = speculate() abc('trm') write_file('spec') status = process_status(status) if status == Unsat: print 'Time for proof = %f sec.'%(time.clock() - x) return RESULT[status] if ((status < Unsat) or (status == Error)): print 'CEX in frame %d'%cex_frame() K = K-1 #if spec found a true cex, then result of abstract was wrong else: abc('w %s_backup_%d.aig'%(initial_f_name,K)) K = K +1 status = final_verify_recur(K) abc('trm') write_file('final') print 'Time for proof = %f sec.'%(time.clock() - x) return RESULT[status] def prove_g_pos(a): """Proves the outputs clustered by a parameter a. a is the disallowed increase in latch support Clusters must be contiguous If a = 0 then outputs are proved individually. Clustering is done from last to first Output 0 is attempted to be proved inductively using other outputs as constraints. Proved outputs are removed if all the outputs have not been proved. If ever one of the proofs returns SAT, we stop and do not try any other outputs.""" global f_name, max_bmc,x_factor x = time.clock() #input_x_factor() init_f_name = f_name #fast_int(1) print 'Beginning prove_g_pos' prove_all_ind() print 'Number of outputs reduced to %d by induction and fast interpolation'%n_pos() print '\n************Running second level prove****************\n' try_rpm() result = prove(1) # 1 here means do not try speculate. #result = prove_0_ind() if result == 'UNSAT': print 'Second prove returned UNSAT' return result if result == 'SAT': print 'CEX found' return result print '\n********** Proving each output separately ************' prove_all_ind() print 'Number of outputs reduced to %d by induction and fast interpolation'%n_pos() f_name = init_f_name abc('w %s_osavetemp.aig'%f_name) n = n_pos() print 'Number of outputs = %d'%n #count = 0 pos_proved = [] J = 0 jnext = n-1 while jnext >= 0: max_bmc = -1 f_name = init_f_name abc('r %s_osavetemp.aig'%f_name) #Do in reverse order jnext_old = jnext if a == 0: # do not group extract(jnext,jnext) jnext = jnext -1 else: jnext = group(a,jnext) if jnext_old > jnext+1: print '\nProving outputs [%d-%d]'%(jnext + 1,jnext_old) else: print '\nProving output %d'%(jnext_old) #ps() #fast_int(1) f_name = f_name + '_%d'%jnext_old result = prove_1() if result == 'UNSAT': if jnext_old > jnext+1: print '\n******** PROVED OUTPUTS [%d-%d] ******** \n\n'%(jnext+1,jnext_old) else: print '\n******** PROVED OUTPUT %d ******** \n\n'%(jnext_old) pos_proved = pos_proved + range(jnext +1,jnext_old+1) continue if result == 'SAT': print 'One of output in (%d to %d) is SAT'%(jnext + 1,jnext_old) return result else: print '\n******** UNDECIDED on OUTPUTS %d thru %d ******** \n\n'%(jnext+1,jnext_old) f_name = init_f_name abc('r %s_osavetemp.aig'%f_name) if not len(pos_proved) == n: print 'Eliminating %d proved outputs'%(len(pos_proved)) remove(pos_proved) abc('trm') write_file('group') result = 'UNDECIDED' else: print 'Proved all outputs. The problem is proved UNSAT' result = 'UNSAT' print 'Total time for prove_g_pos = %f sec.'%(time.clock() - x) return result def prove_pos(): """ Proved outputs are removed if all the outputs have not been proved. If ever one of the proofs returns SAT, we stop and do not try any other outputs.""" global f_name, max_bmc,x_factor x = time.clock() #input_x_factor() init_f_name = f_name #fast_int(1) print 'Beginning prove_pos' prove_all_ind() print 'Number of outputs reduced to %d by induction and fast interpolation'%n_pos() print '\n********** Proving each output separately ************' f_name = init_f_name abc('w %s_osavetemp.aig'%f_name) n = n_pos() print 'Number of outputs = %d'%n #count = 0 pos_proved = [] pos_disproved = [] J = 0 jnext = n-1 while jnext >= 0: max_bmc = -1 f_name = init_f_name abc('r %s_osavetemp.aig'%f_name) #Do in reverse order jnext_old = jnext extract(jnext,jnext) jnext = jnext -1 print '\nProving output %d'%(jnext_old) f_name = f_name + '_%d'%jnext_old result = prove_1() if result == 'UNSAT': print '\n******** PROVED OUTPUT %d ******** \n\n'%(jnext_old) pos_proved = pos_proved + range(jnext +1,jnext_old+1) continue if result == 'SAT': print '\n******** DISPROVED OUTPUT %d ******** \n\n'%(jnext_old) pos_disproved = pos_disproved + range(jnext +1,jnext_old+1) continue else: print '\n******** UNDECIDED on OUTPUT %d ******** \n\n'%(jnext_old) f_name = init_f_name abc('r %s_osavetemp.aig'%f_name) list = pos_proved + pos_disproved print 'Proved the following outputs: %s'%pos_proved print 'Disproved the following outputs: %s'%pos_disproved if not len(list) == n: print 'Eliminating %d resolved outputs'%(len(list)) remove(list) abc('trm') write_file('group') result = 'UNRESOLVED' else: print 'Proved or disproved all outputs. The problem is proved RESOLVED' result = 'RESOLVED' print 'Total time for prove_pos = %f sec.'%(time.clock() - x) return result def prove_g_pos_split(): """like prove_g_pos but quits when any output is undecided""" global f_name, max_bmc,x_factor x = time.clock() #input_x_factor() init_f_name = f_name #fast_int(1) print 'Beginning prove_g_pos_split' prove_all_ind() print 'Number of outputs reduced to %d by induction and fast interpolation'%n_pos() try_rpm() print '\n********** Proving each output separately ************' f_name = init_f_name abc('w %s_osavetemp.aig'%f_name) n = n_pos() print 'Number of outputs = %d'%n pos_proved = [] J = 0 jnext = n-1 while jnext >= 0: max_bmc = -1 f_name = init_f_name abc('r %s_osavetemp.aig'%f_name) jnext_old = jnext extract(jnext,jnext) jnext = jnext -1 print '\nProving output %d'%(jnext_old) f_name = f_name + '_%d'%jnext_old result = prove_1() if result == 'UNSAT': if jnext_old > jnext+1: print '\n******** PROVED OUTPUTS [%d-%d] ******** \n\n'%(jnext+1,jnext_old) else: print '\n******** PROVED OUTPUT %d ******** \n\n'%(jnext_old) pos_proved = pos_proved + range(jnext +1,jnext_old+1) continue if result == 'SAT': print 'One of output in (%d to %d) is SAT'%(jnext + 1,jnext_old) return result else: print '\n******** UNDECIDED on OUTPUTS %d thru %d ******** \n\n'%(jnext+1,jnext_old) print 'Eliminating %d proved outputs'%(len(pos_proved)) # remove outputs proved and return f_name = init_f_name abc('r %s_osavetemp.aig'%f_name) remove(pos_proved) abc('trm') write_file('group') return 'UNDECIDED' f_name = init_f_name abc('r %s_osavetemp.aig'%f_name) if not len(pos_proved) == n: print 'Eliminating %d proved outputs'%(len(pos_proved)) remove(pos_proved) abc('trm') write_file('group') result = 'UNDECIDED' else: print 'Proved all outputs. The problem is proved UNSAT' result = 'UNSAT' print 'Total time = %f sec.'%(time.clock() - x) return result def group(a,n): """Groups together outputs beginning at output n and any contiguous preceeding output that does not increase the latch support by a or more""" global f_name, max_bmc nlt = n_latches() extract(n,n) nli = n_latches() if n == 0: return n-1 for J in range(1,n+1): abc('r %s_osavetemp.aig'%f_name) j = n-J #print 'Running %d to %d'%(j,n) extract(j,n) #print 'n_latches = %d'%n_latches() #if n_latches() >= nli + (nlt - nli)/2: if n_latches() == nli: continue if n_latches() > nli+a: break abc('r %s_osavetemp.aig'%f_name) ## if j == 1: ## j = j-1 print 'extracting [%d-%d]'%(j,n) extract(j,n) ps() return j-1 def extract(n1,n2): """Extracts outputs n1 through n2""" no = n_pos() if n2 > no: return 'range exceeds number of POs' abc('cone -s -O %d -R %d'%(n1, 1+n2-n1)) abc('scl') def prove_0_ind(): """Uses all other outputs as constraints to try to prove output 0 by induction""" abc('w %s_osavetemp.aig'%f_name) #ps() abc('constr -N %d'%(n_pos()-1)) #ps() abc('fold') #ps() abc('ind -u -C 1000000 -F 20') status = get_status() abc('r %s_osavetemp.aig'%f_name) return status def remove(list): """Removes outputs in list""" zero(list) abc('&get;&trim;&put') #fast_int(1) def zero(list): """Zeros out POs in list""" for j in list: run_command('zeropo -N %d'%j) def sp(): """Alias for super_prove""" print 'Executing super_prove' result = super_prove() return result def super_prove(): """Main proof technique now. Does original prove and if after speculation there are multiple output left if will try to prove each output separately, in reverse order. It will quit at the first output that fails to be proved, or any output that is proved SAT""" global max_bmc, init_initial_f_name, initial_f_name init_initial_f_name = initial_f_name if x_factor > 1: print 'x_factor = %d'%x_factor input_x_factor() max_bmc = -1 x = time.clock() print "Trying BMC for 2 sec." abc("&get; ,bmc -vt=2") if is_sat(): print 'Total time taken by super_prove = %f sec.'%(time.clock() - x) return 'SAT' result = prove(0) if ((result[:3] == 'UND') and (n_latches() == 0)): return result k = 1 print result if not result[:3] == 'UND': print 'Total time taken by super_prove = %f sec.'%(time.clock() - x) return result if n_pos() > 1: result = prove_g_pos(0) print result if result == 'UNSAT': print 'Total time taken by super_prove = %f sec.'%(time.clock() - x) return result if result == 'SAT': k = 0 #Don't try to prove UNSAT on an abstraction that had SAT # should go back to backup 1 since probably spec was bad. y = time.clock() result = BMC_VER_result(k) print 'Total time taken by last gasp verification = %f sec.'%(time.clock() - y) print 'Total time for %s = %f sec.'%(init_initial_f_name,(time.clock() - x)) return result def reachm(t): x = time.clock() run_command('&get;&reach -vcs -T %d;&put'%t) print 'Time = %f'%(time.clock() - x) def reachx(t): x = time.clock() run_command('reachx -t %d'%t) print 'Time = %f'%(time.clock() - x) def BMC_VER_result(n): global init_initial_f_name #print init_initial_f_name xt = time.clock() result = 5 T = 150 if n == 0: abc('r %s_smp.aig'%init_initial_f_name) print '\n***Running proof on initial simplified circuit\n', ps() else: print '\n***Running proof on final unproved circuit' ps() print ' Running PDR for %d sec'%T abc('&get;,pdr -vt=%d'%(T*.8)) result = get_status() if result == Unsat: return 'UNSAT' if result > Unsat: #still undefined if (n_pis()+n_latches() < 250): print ' Running Reachability for 150 sec.' abc('reachx -t 150') #run_command('&get;&reach -vcs -T %d'%T) result = get_status() if result == Unsat: return 'UNSAT' if ((result > Unsat) and n ==1): print ' Running interpolation for %f sec.'%T abc(',imc -vt=%f'%T) result = get_status() if result == Unsat: return 'UNSAT' # if n=1 we are trying to prove result on abstracted circuit. If still undefined, then probably does # not make sense to try pdr, reach, int on original simplified circuit, only BMC here. if n == 1: abc('r %s_smp.aig'%init_initial_f_name) #check if the initial circuit was SAT #print 'Reading %s_smp'%init_initial_f_name, #run_command('bmc3 -v -T %d -F 200000 -C 1000000'%T) print '***Running BMC on initial simplified circuit' ps() print '\n' abc('&get;,bmc -vt=%f'%T) result = get_status() if result < Unsat: result = 'SAT' print ' CEX found in frame %d'%cex_frame() else: result = 'UNDECIDED' print 'Additional time taken by BMC/PDR/Reach = %f sec.'%(time.clock() - xt) return result def try_split(): abc('w %s_savetemp.aig'%f_name) na = n_ands() split(3) if n_ands()> 2*na: abc('r %s_savetemp.aig'%f_name) def time_diff(): global last_time new_time = time.clock() diff = new_time - last_time last_time = new_time result = 'Lapsed time = %.2f sec.'%diff return result def prove_all_ind(): """Tries to prove output k by induction, using other outputs as constraints. If ever an output is proved it is set to 0 so it can't be used in proving another output to break circularity. Finally all zero'ed ooutputs are removed. """ N = n_pos() remove_0_pos() print '0 valued output removal changed POs from %d to %d'%(N,n_pos()) abc('w %s_osavetemp.aig'%f_name) list = range(n_pos()) for j in list: #abc('r %s_osavetemp.aig'%f_name) abc('swappos -N %d'%j) remove_0_pos() #may not have to do this if constr works well with 0'ed outputs abc('constr -N %d'%(n_pos()-1)) abc('fold') n = max(1,n_ands()) f = max(1,min(40000/n,16)) f = int(f) abc('ind -u -C 10000 -F %d'%f) status = get_status() abc('r %s_osavetemp.aig'%f_name) if status == Unsat: print '+', abc('zeropo -N %d'%j) abc('w %s_osavetemp.aig'%f_name) #if changed, store it permanently print '%d'%j, remove_0_pos() print '\nThe number of POs reduced from %d to %d'%(N,n_pos()) #return status def prove_all_pdr(t): """Tries to prove output k by PDR. If ever an output is proved it is set to 0. Finally all zero'ed ooutputs are removed. """ N = n_pos() remove_0_pos() print '0 valued output removal changed POs from %d to %d'%(N,n_pos()) abc('w %s_osavetemp.aig'%f_name) list = range(n_pos()) for j in list: #abc('r %s_osavetemp.aig'%f_name) abc('cone -O %d -s'%j) abc('scl') abc('&get;,pdr -vt=%d'%t) status = get_status() abc('r %s_osavetemp.aig'%f_name) if status == Unsat: print '+', abc('zeropo -N %d'%j) abc('w %s_osavetemp.aig'%f_name) #if changed, store it permanently print '%d'%j, remove_0_pos() print '\nThe number of POs reduced from %d to %d'%(N,n_pos()) #return status def remove_0_pos(): abc('&get; &trim; &put') def prove_all_ind2(): """Tries to prove output k by induction, using outputs > k as constraints. Removes proved outputs from POs.""" abc('w %s_osavetemp.aig'%f_name) plist = [] list = range(n_pos()) ## if r == 1: ## list.reverse() for j in list: abc('r %s_osavetemp.aig'%f_name) extract(j,n_pos()) abc('constr -N %d'%(n_pos()-1)) abc('fold') n = max(1,n_ands()) f = max(1,min(40000/n,16)) f = int(f) abc('ind -u -C 10000 -F %d'%f) status = get_status() if status == Unsat: plist = plist + [j] print '-', ## else: ## status = pdr(1) ## if status == Unsat: ## print '+', ## plist = plist + [j] print '%d'%j, print '\nOutputs proved = ', print plist abc('r %s_osavetemp.aig'%f_name) remove(plist) #remove the outputs proved ## #the following did not work because abc command constr, allows only last set of outputs to be constraints ## abc('w %s_osavetemp.aig'%f_name) ## plist = [] ## list = range(n_pos()) ## list.reverse() ## for j in list: ## abc('r %s_osavetemp.aig'%f_name) ## extract(j,n_pos()) ## abc('constr -N %d'%(n_pos()-1)) ## abc('fold') ## n = max(1,n_ands()) ## f = max(1,min(40000/n,16)) ## f = int(f) ## abc('ind -u -C 10000 -F %d'%f) ## status = get_status() ## if status == Unsat: ## plist = plist + [j] ## print '-', #### else: #### status = pdr(1) #### if status == Unsat: #### print '+', #### plist = plist + [j] ## print '%d'%j, ## print '\nOutputs proved = ', ## print plist.reverse ## abc('r %s_osavetemp.aig'%f_name) ## remove(plist) #remove the outputs proved ## return status def pdr(t): abc('&get; ,pdr -vt=%f'%t) result = get_status() def split(n): abc('orpos;&get') abc('&posplit -v -N %d;&put;dc2;trm'%n) def keep_splitting(): for j in range(5): split(5+j) no = n_pos() status = prove_g_pos_split(0) if status <= Unsat: return status if no == n_pos(): return Undecided def drill(n): run_command('&get; &reach -vcs -H 5 -S %d -T 50 -C 40'%n) def prove_1(): """Proves all the outputs together. If ever an abstraction was done then if SAT is returned, we make RESULT return "undecided". """ a = 1 global x_factor,xfi,f_name x = time.clock() max_bmc = -1 K = 0 print 'Initial: ', print_circuit_stats() x_factor = xfi print 'x_factor = %f'%x_factor print '\n***Running pre_simp' set_globals() status = pre_simp() if ((status <= Unsat) or (n_latches == 0)): print 'Time for proof = %f sec.'%(time.clock() - x) return RESULT[status] abc('trm') write_file('smp') abc('w %s_backup_%d.aig'%(initial_f_name,K)) K = K +1 set_globals() if ((n_ands() < 30000) and (a == 1) and (n_latches() < 300)): print '\n***Running quick_verify' status = quick_verify(0) if status <= Unsat: if not status == Unsat: print 'CEX in frame %d'%cex_frame() print 'Time for proof = %f sec.'%(time.clock() - x) return RESULT[status] print'\n***Running abstract' nl_b = n_latches() status = abstract() abc('trm') write_file('abs') status = process_status(status) if ((status <= Unsat) or status == Error): if status < Unsat: print 'CEX in frame %d'%cex_frame() print 'Time for proof = %f sec.'%(time.clock() - x) return RESULT[status] print 'Time for proof = %f sec.'%(time.clock() - x) return RESULT[status] abc('w %s_backup_%d.aig'%(initial_f_name,K)) status = final_verify_recur(2) abc('trm') write_file('final') print 'Time for proof = %f sec.'%(time.clock() - x) return RESULT[status] def qprove(): global x_factor x = time.clock() x_factor = 3 print '\n*********pre_simp**********\n' pre_simp() print '\n*********absv**********\n' result = absv(3,1) x_factor = 2 print '\n*********absv**********\n' result = absv(3,1) print '\n*********speculate**********\n' result = speculate() if result <= Unsat: return RESULT[result] print '\n*********absv**********\n' result = absv(3,1) print '\n*********prove_pos**********\n' result = prove_pos() if result == 'UNDECIDED': print '\n*********BMC_VER_result**********\n' result = BMC_VER_result(1) print 'Time for proof = %f sec.'%(time.clock() - x) return result def pre_reduce(): x = time.clock() pre_simp() write_file('smp') abstract() write_file('abs') print 'Time = %f'%(time.clock() - x) #PARALLEL FUNCTIONS """ funcs should look like funcs = [defer(abc)('&get;,bmc -vt=50;&put'),defer(super_prove)()] After this is executed funcs becomes a special list of lambda functions which are given to abc_split_all to be executed as in fork below. It has been set up so that each of the functions works on the current aig and possibly transforms it. The new aig and status is always read into the master when done """ def fork(funcs): """ runs funcs in parallel""" for i,res in pyabc_split.abc_split_all(funcs): status = prob_status() if not status == -1: print i,status ps() break else: print i,status ps() continue return status def handler_s(res): """ This serial handler returns True if the problem is solved by the first returning function, in which case, the problem is replaced by the new aig and status. """ if not res == -1: #replace_prob() print ('UNSAT','SAT')[res] return True else: return False