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flops.py
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#!/usr/local/bin/python
#/*****************************/
#/* flops.c */
#/* Version 2.0, 18 Dec 1992 */
#/* Al Aburto */
#/* [email protected] */
#/*****************************/
__author__ = 'Brian Olson'
# modified by CycleUser
"""
/*
Flops.c is a 'c' program which attempts to estimate your systems
floating-point 'MFLOPS' rating for the FADD, FSUB, FMUL, and FDIV
operations based on specific 'instruction mixes' (discussed below).
The program provides an estimate of PEAK MFLOPS performance by making
maximal use of register variables with minimal interaction with main
memory. The execution loops are all small so that they will fit in
any cache. Flops.c can be used along with Linpack and the Livermore
kernels (which exersize memory much more extensively) to gain further
insight into the limits of system performance. The flops.c execution
modules also include various percent weightings of FDIV's (from 0% to
25% FDIV's) so that the range of performance can be obtained when
using FDIV's. FDIV's, being computationally more intensive than
FADD's or FMUL's, can impact performance considerably on some systems.
Flops.c consists of 8 independent modules (routines) which, except for
module 2, conduct numerical integration of various functions. Module
2, estimates the value of pi based upon the Maclaurin series expansion
of atan(1). MFLOPS ratings are provided for each module, but the
programs overall results are summerized by the MFLOPS(1), MFLOPS(2),
MFLOPS(3), and MFLOPS(4) outputs.
The MFLOPS(1) result is identical to the result provided by all
previous versions of flops.c. It is based only upon the results from
modules 2 and 3. Two problems surfaced in using MFLOPS(1). First, it
was difficult to completely 'vectorize' the result due to the
recurrence of the 's' variable in module 2. This problem is addressed
in the MFLOPS(2) result which does not use module 2, but maintains
nearly the same weighting of FDIV's (9.2%) as in MFLOPS(1) (9.6%).
The second problem with MFLOPS(1) centers around the percentage of
FDIV's (9.6%) which was viewed as too high for an important class of
problems. This concern is addressed in the MFLOPS(3) result where NO
FDIV's are conducted at all.
The number of floating-point instructions per iteration (loop) is
given below for each module executed:
MODULE FADD FSUB FMUL FDIV TOTAL Comment
1 7 0 6 1 14 7.1% FDIV's
2 3 2 1 1 7 difficult to vectorize.
3 6 2 9 0 17 0.0% FDIV's
4 7 0 8 0 15 0.0% FDIV's
5 13 0 15 1 29 3.4% FDIV's
6 13 0 16 0 29 0.0% FDIV's
7 3 3 3 3 12 25.0% FDIV's
8 13 0 17 0 30 0.0% FDIV's
A*2+3 21 12 14 5 52 A=5, MFLOPS(1), Same as
40.4% 23.1% 26.9% 9.6% previous versions of the
flops.c program. Includes
only Modules 2 and 3, does
9.6% FDIV's, and is not
easily vectorizable.
1+3+4 58 14 66 14 152 A=4, MFLOPS(2), New output
+5+6+ 38.2% 9.2% 43.4% 9.2% does not include Module 2,
A*7 but does 9.2% FDIV's.
1+3+4 62 5 74 5 146 A=0, MFLOPS(3), New output
+5+6+ 42.9% 3.4% 50.7% 3.4% does not include Module 2,
7+8 but does 3.4% FDIV's.
3+4+6 39 2 50 0 91 A=0, MFLOPS(4), New output
+8 42.9% 2.2% 54.9% 0.0% does not include Module 2,
and does NO FDIV's.
NOTE: Various timer routines are included as indicated below. The
timer routines, with some comments, are attached at the end
of the main program.
NOTE: Please do not remove any of the printouts.
EXAMPLE COMPILATION:
UNIX based systems
cc -DUNIX -O flops.c -o flops
cc -DUNIX -DROPT flops.c -o flops
cc -DUNIX -fast -O4 flops.c -o flops
.
.
.
etc.
Al Aburto
*/
"""
import math
import time
def dtime(p):
q = p[2]
p[2] = time.time()
p[1] = p[2] - q
def main():
TimeArray = [0.0, 0.0, 0.0]
#double nulltime, TimeArray[3]; /* Variables needed for 'dtime()'. */
#double TLimit; /* Threshold to determine Number of */
# /* Loops to run. Fixed at 15.0 seconds.*/
T = [0.0 for x in range(36)]
#double T[36]; /* Global Array used to hold timing */
# /* results and other information. */
#double sa,sb,sc,sd,one,two,three;
#double four,five,piref,piprg;
#double scale,pierr;
A0 = 1.0
A1 = -0.1666666666671334
A2 = 0.833333333809067E-2
A3 = 0.198412715551283E-3
A4 = 0.27557589750762E-5
A5 = 0.2507059876207E-7
A6 = 0.164105986683E-9
B0 = 1.0
B1 = -0.4999999999982
B2 = 0.4166666664651E-1
B3 = -0.1388888805755E-2
B4 = 0.24801428034E-4
B5 = -0.2754213324E-6
B6 = 0.20189405E-8
C0 = 1.0
C1 = 0.99999999668
C2 = 0.49999995173
C3 = 0.16666704243
C4 = 0.4166685027E-1
C5 = 0.832672635E-2
C6 = 0.140836136E-2
C7 = 0.17358267E-3
C8 = 0.3931683E-4
D1 = 0.3999999946405E-1
D2 = 0.96E-3
D3 = 0.1233153E-5
E2 = 0.48E-3
E3 = 0.411051E-6
print("\n")
print(" FLOPS Python Program (Double Precision), V2.0 18 Dec 1992\n\n")
# Initial number of loops. Original code claims this is a magic number.
loops = 15625
#/****************************************************/
#/* Set Variable Values. */
#/* T[1] references all timing results relative to */
#/* one million loops. */
#/* */
#/* The program will execute from 31250 to 512000000 */
#/* loops based on a runtime of Module 1 of at least */
#/* TLimit = 15.0 seconds. That is, a runtime of 15 */
#/* seconds for Module 1 is used to determine the */
#/* number of loops to execute. */
#/* */
#/* No more than NLimit = 512000000 loops are allowed*/
#/****************************************************/
T[1] = 1.0E+06/loops
TLimit = 15.0
NLimit = 512000000
piref = 3.14159265358979324
one = 1.0
two = 2.0
three = 3.0
four = 4.0
five = 5.0
scale = one
print(" Module Error RunTime MFLOPS\n")
print(" (usec)\n")
#/*************************/
#/* Initialize the timer. */
#/*************************/
dtime(TimeArray)
dtime(TimeArray)
#/*******************************************************/
#/* Module 1. Calculate integral of df(x)/f(x) defined */
#/* below. Result is ln(f(1)). There are 14 */
#/* double precision operations per loop */
#/* ( 7 +, 0 -, 6 *, 1 / ) that are included */
#/* in the timing. */
#/* 50.0% +, 00.0% -, 42.9% *, and 07.1% / */
#/*******************************************************/
n = loops
sa = 0.0
while sa < TLimit:
n = 2 * n
x = one / n # /*********************/
s = 0.0 # /* Loop 1. */
v = 0.0 # /*********************/
w = one
dtime(TimeArray)
for i in range(1,n):
v = v + w
u = v * x
s = s + (D1+u*(D2+u*D3))/(w+u*(D1+u*(E2+u*E3)))
dtime(TimeArray)
sa = TimeArray[1]
if n == NLimit:
break
#/* printf(" %10ld %12.5lf\n",n,sa); */
scale = 1.0E+06 / n
T[1] = scale
#/****************************************/
#/* Estimate nulltime ('for' loop time). */
#/****************************************/
dtime(TimeArray)
for i in range(1, n):
pass
dtime(TimeArray)
nulltime = T[1] * TimeArray[1]
if nulltime < 0.0:
nulltime = 0.0
T[2] = T[1] * sa - nulltime
sa = (D1+D2+D3)/(one+D1+E2+E3)
sb = D1
T[3] = T[2] / 14.0# /*********************/
sa = x * ( sa + sb + two * s ) / two# /* Module 1 Results. */
sb = one / sa# /*********************/
n = int( ( 40000 * sb ) / scale )
sc = sb - 25.2
T[4] = one / T[3]
# /********************/
# /* DO NOT REMOVE */
# /* THIS PRINTOUT! */
#// printf(" 1 %13.4le %10.4lf %10.4lf\n",sc,T[2],T[4])
print (" 1 %13.4e %10.4f %10.4f\n" % (sc,T[2],T[4]))
m = n
#/*******************************************************/
#/* Module 2. Calculate value of PI from Taylor Series */
#/* expansion of atan(1.0). There are 7 */
#/* double precision operations per loop */
#/* ( 3 +, 2 -, 1 *, 1 / ) that are included */
#/* in the timing. */
#/* 42.9% +, 28.6% -, 14.3% *, and 14.3% / */
#/*******************************************************/
s = -five# /********************/
sa = -one# /* Loop 2. */
# /********************/
dtime(TimeArray)
for i in range(1, m+1):
s = -s
sa = sa + s
dtime(TimeArray)
T[5] = T[1] * TimeArray[1]
if T[5] < 0.0:
T[5] = 0.0
sc = m
u = sa# /*********************/
v = 0.0# /* Loop 3. */
w = 0.0# /*********************/
x = 0.0
dtime(TimeArray)
for i in range(1, m+1):
s = -s
sa = sa + s
u = u + two
x = x +(s - u)
v = v - s * u
w = w + s / u
dtime(TimeArray)
T[6] = T[1] * TimeArray[1]
T[7] = ( T[6] - T[5] ) / 7.0# /*********************/
m = int( sa * x / sc )# /* PI Results */
sa = four * w / five# /*********************/
sb = sa + five / v
sc = 31.25
piprg = sb - sc / (v * v * v)
pierr = piprg - piref
T[8] = one / T[7]
# /*********************/
# /* DO NOT REMOVE */
# /* THIS PRINTOUT! */
# /*********************/
print (" 2 %13.4e %10.4f %10.4f\n" % (pierr,T[6]-T[5],T[8]))
#/*******************************************************/
#/* Module 3. Calculate integral of sin(x) from 0.0 to */
#/* PI/3.0 using Trapazoidal Method. Result */
#/* is 0.5. There are 17 double precision */
#/* operations per loop (6 +, 2 -, 9 *, 0 /) */
#/* included in the timing. */
#/* 35.3% +, 11.8% -, 52.9% *, and 00.0% / */
#/*******************************************************/
x = piref / ( three * m )# /*********************/
s = 0.0# /* Loop 4. */
v = 0.0# /*********************/
dtime(TimeArray)
for i in range(1, m):
v = v + one
u = v * x
w = u * u
s = s + u * ((((((A6*w-A5)*w+A4)*w-A3)*w+A2)*w+A1)*w+one)
dtime(TimeArray)
T[9] = T[1] * TimeArray[1] - nulltime
u = piref / three
w = u * u
sa = u * ((((((A6*w-A5)*w+A4)*w-A3)*w+A2)*w+A1)*w+one)
T[10] = T[9] / 17.0# /*********************/
sa = x * ( sa + two * s ) / two# /* sin(x) Results. */
sb = 0.5# /*********************/
sc = sa - sb
T[11] = one / T[10]
# /*********************/
# /* DO NOT REMOVE */
# /* THIS PRINTOUT! */
# /*********************/
print (" 3 %13.4e %10.4f %10.4f\n" % (sc,T[9],T[11]))
#/************************************************************/
#/* Module 4. Calculate Integral of cos(x) from 0.0 to PI/3 */
#/* using the Trapazoidal Method. Result is */
#/* sin(PI/3). There are 15 double precision */
#/* operations per loop (7 +, 0 -, 8 *, and 0 / ) */
#/* included in the timing. */
#/* 50.0% +, 00.0% -, 50.0% *, 00.0% / */
#/************************************************************/
A3 = -A3
A5 = -A5
x = piref / ( three * m )# /*********************/
s = 0.0# /* Loop 5. */
v = 0.0# /*********************/
dtime(TimeArray)
for i in range(1, m):
u = i * x
w = u * u
s = s + w*(w*(w*(w*(w*(B6*w+B5)+B4)+B3)+B2)+B1)+one
dtime(TimeArray)
T[12] = T[1] * TimeArray[1] - nulltime
u = piref / three
w = u * u
sa = w*(w*(w*(w*(w*(B6*w+B5)+B4)+B3)+B2)+B1)+one
T[13] = T[12] / 15.0# /*******************/
sa = x * ( sa + one + two * s ) / two# /* Module 4 Result */
u = piref / three# /*******************/
w = u * u
sb = u * ((((((A6*w+A5)*w+A4)*w+A3)*w+A2)*w+A1)*w+A0)
sc = sa - sb
T[14] = one / T[13]
# /*********************/
# /* DO NOT REMOVE */
# /* THIS PRINTOUT! */
# /*********************/
print (" 4 %13.4e %10.4f %10.4f\n" % (sc,T[12],T[14]))
#/************************************************************/
#/* Module 5. Calculate Integral of tan(x) from 0.0 to PI/3 */
#/* using the Trapazoidal Method. Result is */
#/* ln(cos(PI/3)). There are 29 double precision */
#/* operations per loop (13 +, 0 -, 15 *, and 1 /)*/
#/* included in the timing. */
#/* 46.7% +, 00.0% -, 50.0% *, and 03.3% / */
#/************************************************************/
x = piref / ( three * m )# /*********************/
s = 0.0# /* Loop 6. */
v = 0.0# /*********************/
dtime(TimeArray)
for i in range(1, m):
u = i * x
w = u * u
v = u * ((((((A6*w+A5)*w+A4)*w+A3)*w+A2)*w+A1)*w+one)
s = s + v / (w*(w*(w*(w*(w*(B6*w+B5)+B4)+B3)+B2)+B1)+one)
dtime(TimeArray)
T[15] = T[1] * TimeArray[1] - nulltime
u = piref / three
w = u * u
sa = u*((((((A6*w+A5)*w+A4)*w+A3)*w+A2)*w+A1)*w+one)
sb = w*(w*(w*(w*(w*(B6*w+B5)+B4)+B3)+B2)+B1)+one
sa = sa / sb
T[16] = T[15] / 29.0# /*******************/
sa = x * ( sa + two * s ) / two# /* Module 5 Result */
sb = 0.6931471805599453# /*******************/
sc = sa - sb
T[17] = one / T[16]
# /*********************/
# /* DO NOT REMOVE */
# /* THIS PRINTOUT! */
# /*********************/
print (" 5 %13.4e %10.4f %10.4f\n" % (sc,T[15],T[17]))
#/************************************************************/
#/* Module 6. Calculate Integral of sin(x)*cos(x) from 0.0 */
#/* to PI/4 using the Trapazoidal Method. Result */
#/* is sin(PI/4)^2. There are 29 double precision */
#/* operations per loop (13 +, 0 -, 16 *, and 0 /)*/
#/* included in the timing. */
#/* 46.7% +, 00.0% -, 53.3% *, and 00.0% / */
#/************************************************************/
x = piref / ( four * m )# /*********************/
s = 0.0# /* Loop 7. */
v = 0.0# /*********************/
dtime(TimeArray)
for i in range(1, m):
u = i * x
w = u * u
v = u * ((((((A6*w+A5)*w+A4)*w+A3)*w+A2)*w+A1)*w+one)
s = s + v*(w*(w*(w*(w*(w*(B6*w+B5)+B4)+B3)+B2)+B1)+one)
dtime(TimeArray)
T[18] = T[1] * TimeArray[1] - nulltime
u = piref / four
w = u * u
sa = u*((((((A6*w+A5)*w+A4)*w+A3)*w+A2)*w+A1)*w+one)
sb = w*(w*(w*(w*(w*(B6*w+B5)+B4)+B3)+B2)+B1)+one
sa = sa * sb
T[19] = T[18] / 29.0# /*******************/
sa = x * ( sa + two * s ) / two# /* Module 6 Result */
sb = 0.25# /*******************/
sc = sa - sb
T[20] = one / T[19]
# /*********************/
# /* DO NOT REMOVE */
# /* THIS PRINTOUT! */
# /*********************/
print (" 6 %13.4e %10.4f %10.4f\n" % (sc,T[18],T[20]))
#/*******************************************************/
#/* Module 7. Calculate value of the definite integral */
#/* from 0 to sa of 1/(x+1), x/(x*x+1), and */
#/* x*x/(x*x*x+1) using the Trapizoidal Rule.*/
#/* There are 12 double precision operations */
#/* per loop ( 3 +, 3 -, 3 *, and 3 / ) that */
#/* are included in the timing. */
#/* 25.0% +, 25.0% -, 25.0% *, and 25.0% / */
#/*******************************************************/
# /*********************/
s = 0.0# /* Loop 8. */
w = one# /*********************/
sa = 102.3321513995275
v = sa / m
dtime(TimeArray)
for i in range(1, m):
x = i * v
u = x * x
s = s - w / ( x + w ) - x / ( u + w ) - u / ( x * u + w )
dtime(TimeArray)
T[21] = T[1] * TimeArray[1] - nulltime
# /*********************/
# /* Module 7 Results */
# /*********************/
T[22] = T[21] / 12.0
x = sa
u = x * x
sa = -w - w / ( x + w ) - x / ( u + w ) - u / ( x * u + w )
sa = 18.0 * v * (sa + two * s )
m = -2000 * int(sa)
m = int( m / scale )
sc = sa + 500.2
T[23] = one / T[22]
# /********************/
# /* DO NOT REMOVE */
# /* THIS PRINTOUT! */
# /********************/
print (" 7 %13.4e %10.4f %10.4f\n" % (sc,T[21],T[23]))
#/************************************************************/
#/* Module 8. Calculate Integral of sin(x)*cos(x)*cos(x) */
#/* from 0 to PI/3 using the Trapazoidal Method. */
#/* Result is (1-cos(PI/3)^3)/3. There are 30 */
#/* double precision operations per loop included */
#/* in the timing: */
#/* 13 +, 0 -, 17 * 0 / */
#/* 46.7% +, 00.0% -, 53.3% *, and 00.0% / */
#/************************************************************/
x = piref / ( three * m )# /*********************/
s = 0.0# /* Loop 9. */
v = 0.0# /*********************/
dtime(TimeArray)
for i in range(1, m):
u = i * x
w = u * u
v = w*(w*(w*(w*(w*(B6*w+B5)+B4)+B3)+B2)+B1)+one
s = s + v*v*u*((((((A6*w+A5)*w+A4)*w+A3)*w+A2)*w+A1)*w+one)
dtime(TimeArray)
T[24] = T[1] * TimeArray[1] - nulltime
u = piref / three
w = u * u
sa = u*((((((A6*w+A5)*w+A4)*w+A3)*w+A2)*w+A1)*w+one)
sb = w*(w*(w*(w*(w*(B6*w+B5)+B4)+B3)+B2)+B1)+one
sa = sa * sb * sb
T[25] = T[24] / 30.0# /*******************/
sa = x * ( sa + two * s ) / two# /* Module 8 Result */
sb = 0.29166666666666667# /*******************/
sc = sa - sb
T[26] = one / T[25]
# /*********************/
# /* DO NOT REMOVE */
# /* THIS PRINTOUT! */
# /*********************/
print (" 8 %13.4e %10.4f %10.4f\n" % (sc,T[24],T[26]))
#/**************************************************/
#/* MFLOPS(1) output. This is the same weighting */
#/* used for all previous versions of the flops.c */
#/* program. Includes Modules 2 and 3 only. */
#/**************************************************/
T[27] = ( five * (T[6] - T[5]) + T[9] ) / 52.0
T[28] = one / T[27]
#/**************************************************/
#/* MFLOPS(2) output. This output does not include */
#/* Module 2, but it still does 9.2% FDIV's. */
#/**************************************************/
T[29] = T[2] + T[9] + T[12] + T[15] + T[18]
T[29] = (T[29] + four * T[21]) / 152.0
T[30] = one / T[29]
#/**************************************************/
#/* MFLOPS(3) output. This output does not include */
#/* Module 2, but it still does 3.4% FDIV's. */
#/**************************************************/
T[31] = T[2] + T[9] + T[12] + T[15] + T[18]
T[31] = (T[31] + T[21] + T[24]) / 146.0
T[32] = one / T[31]
#/**************************************************/
#/* MFLOPS(4) output. This output does not include */
#/* Module 2, and it does NO FDIV's. */
#/**************************************************/
T[33] = (T[9] + T[12] + T[18] + T[24]) / 91.0
T[34] = one / T[33]
print ("\n")
print (" Iterations = %10d\n" % m)
print (" NullTime (usec) = %10.4f\n" % nulltime)
print (" MFLOPS(1) = %10.4f\n" % T[28])
print (" MFLOPS(2) = %10.4f\n" % T[30])
print (" MFLOPS(3) = %10.4f\n" % T[32])
print (" MFLOPS(4) = %10.4f\n\n" % T[34])
if __name__ == "__main__":
main()