!-------------------------------------------------------------------------! ! ! ! N A S P A R A L L E L B E N C H M A R K S 3.3 ! ! ! ! S E R I A L V E R S I O N ! ! ! ! E P ! ! ! !-------------------------------------------------------------------------! ! ! ! This benchmark is a serial version of the NPB EP code. ! ! Refer to NAS Technical Reports 95-020 for details. ! ! ! ! Permission to use, copy, distribute and modify this software ! ! for any purpose with or without fee is hereby granted. We ! ! request, however, that all derived work reference the NAS ! ! Parallel Benchmarks 3.3. This software is provided "as is" ! ! without express or implied warranty. ! ! ! ! Information on NPB 3.3, including the technical report, the ! ! original specifications, source code, results and information ! ! on how to submit new results, is available at: ! ! ! ! http://www.nas.nasa.gov/Software/NPB/ ! ! ! ! Send comments or suggestions to npb@nas.nasa.gov ! ! ! ! NAS Parallel Benchmarks Group ! ! NASA Ames Research Center ! ! Mail Stop: T27A-1 ! ! Moffett Field, CA 94035-1000 ! ! ! ! E-mail: npb@nas.nasa.gov ! ! Fax: (650) 604-3957 ! ! ! !-------------------------------------------------------------------------! c--------------------------------------------------------------------- c c Author: P. O. Frederickson c D. H. Bailey c A. C. Woo c--------------------------------------------------------------------- c--------------------------------------------------------------------- program EMBAR c--------------------------------------------------------------------- C c This is the serial version of the APP Benchmark 1, c the "embarassingly parallel" benchmark. c c c M is the Log_2 of the number of complex pairs of uniform (0, 1) random c numbers. MK is the Log_2 of the size of each batch of uniform random c numbers. MK can be set for convenience on a given system, since it does c not affect the results. implicit none include 'npbparams.h' double precision Mops, epsilon, a, s, t1, t2, t3, t4, x, x1, > x2, q, sx, sy, tm, an, tt, gc, dum(3) double precision sx_verify_value, sy_verify_value, sx_err, sy_err integer mk, mm, nn, nk, nq, np, > i, ik, kk, l, k, nit, > k_offset, j, fstatus logical verified, timers_enabled external randlc, timer_read double precision randlc, timer_read character*15 size parameter (mk = 16, mm = m - mk, nn = 2 ** mm, > nk = 2 ** mk, nq = 10, epsilon=1.d-8, > a = 1220703125.d0, s = 271828183.d0) common/storage/ x(2*nk), q(0:nq-1) data dum /1.d0, 1.d0, 1.d0/ open(unit=2, file='timer.flag', status='old', iostat=fstatus) if (fstatus .eq. 0) then timers_enabled = .true. close(2) else timers_enabled = .false. endif c Because the size of the problem is too large to store in a 32-bit c integer for some classes, we put it into a string (for printing). c Have to strip off the decimal point put in there by the floating c point print statement (internal file) write(*, 1000) write(size, '(f15.0)' ) 2.d0**(m+1) j = 15 if (size(j:j) .eq. '.') j = j - 1 write (*,1001) size(1:j) write (*,*) 1000 format(//,' NAS Parallel Benchmarks (NPB3.3-SER)', > ' - EP Benchmark', /) 1001 format(' Number of random numbers generated: ', a15) verified = .false. c Compute the number of "batches" of random number pairs generated c per processor. Adjust if the number of processors does not evenly c divide the total number np = nn c Call the random number generator functions and initialize c the x-array to reduce the effects of paging on the timings. c Also, call all mathematical functions that are used. Make c sure these initializations cannot be eliminated as dead code. call vranlc(0, dum(1), dum(2), dum(3)) dum(1) = randlc(dum(2), dum(3)) do 5 i = 1, 2*nk x(i) = -1.d99 5 continue Mops = log(sqrt(abs(max(1.d0,1.d0)))) call timer_clear(1) call timer_clear(2) call timer_clear(3) call timer_start(1) t1 = a call vranlc(0, t1, a, x) c Compute AN = A ^ (2 * NK) (mod 2^46). t1 = a do 100 i = 1, mk + 1 t2 = randlc(t1, t1) 100 continue an = t1 tt = s gc = 0.d0 sx = 0.d0 sy = 0.d0 do 110 i = 0, nq - 1 q(i) = 0.d0 110 continue c Each instance of this loop may be performed independently. We compute c the k offsets separately to take into account the fact that some nodes c have more numbers to generate than others k_offset = -1 do 150 k = 1, np kk = k_offset + k t1 = s t2 = an c Find starting seed t1 for this kk. do 120 i = 1, 100 ik = kk / 2 if (2 * ik .ne. kk) t3 = randlc(t1, t2) if (ik .eq. 0) goto 130 t3 = randlc(t2, t2) kk = ik 120 continue c Compute uniform pseudorandom numbers. 130 continue if (timers_enabled) call timer_start(3) call vranlc(2 * nk, t1, a, x) if (timers_enabled) call timer_stop(3) c Compute Gaussian deviates by acceptance-rejection method and c tally counts in concentric square annuli. This loop is not c vectorizable. if (timers_enabled) call timer_start(2) do 140 i = 1, nk x1 = 2.d0 * x(2*i-1) - 1.d0 x2 = 2.d0 * x(2*i) - 1.d0 t1 = x1 ** 2 + x2 ** 2 if (t1 .le. 1.d0) then t2 = sqrt(-2.d0 * log(t1) / t1) t3 = (x1 * t2) t4 = (x2 * t2) l = max(abs(t3), abs(t4)) q(l) = q(l) + 1.d0 sx = sx + t3 sy = sy + t4 endif 140 continue if (timers_enabled) call timer_stop(2) 150 continue do 160 i = 0, nq - 1 gc = gc + q(i) 160 continue call timer_stop(1) tm = timer_read(1) nit=0 verified = .true. if (m.eq.24) then sx_verify_value = -3.247834652034740D+3 sy_verify_value = -6.958407078382297D+3 elseif (m.eq.25) then sx_verify_value = -2.863319731645753D+3 sy_verify_value = -6.320053679109499D+3 elseif (m.eq.28) then sx_verify_value = -4.295875165629892D+3 sy_verify_value = -1.580732573678431D+4 elseif (m.eq.30) then sx_verify_value = 4.033815542441498D+4 sy_verify_value = -2.660669192809235D+4 elseif (m.eq.32) then sx_verify_value = 4.764367927995374D+4 sy_verify_value = -8.084072988043731D+4 elseif (m.eq.36) then sx_verify_value = 1.982481200946593D+5 sy_verify_value = -1.020596636361769D+5 elseif (m.eq.40) then sx_verify_value = -5.319717441530D+05 sy_verify_value = -3.688834557731D+05 else verified = .false. endif if (verified) then sx_err = abs((sx - sx_verify_value)/sx_verify_value) sy_err = abs((sy - sy_verify_value)/sy_verify_value) verified = ((sx_err.le.epsilon) .and. (sy_err.le.epsilon)) endif Mops = 2.d0**(m+1)/tm/1000000.d0 write (6,11) tm, m, gc, sx, sy, (i, q(i), i = 0, nq - 1) 11 format ('EP Benchmark Results:'//'CPU Time =',f10.4/'N = 2^', > i5/'No. Gaussian Pairs =',f15.0/'Sums = ',1p,2d25.15/ > 'Counts:'/(i3,0p,f15.0)) call print_results('EP', class, m+1, 0, 0, nit, > tm, Mops, > 'Random numbers generated', > verified, npbversion, compiletime, cs1, > cs2, cs3, cs4, cs5, cs6, cs7) if (timers_enabled) then if (tm .le. 0.d0) tm = 1.0 tt = timer_read(1) print 810, 'Total time: ', tt, tt*100./tm tt = timer_read(2) print 810, 'Gaussian pairs:', tt, tt*100./tm tt = timer_read(3) print 810, 'Random numbers:', tt, tt*100./tm 810 format(1x,a,f9.3,' (',f6.2,'%)') endif end