<< Chapter < Page Chapter >> Page >

Why is an unrolling amount of three or four iterations generally sufficient for simple vector loops on a RISC processor? What relationship does the unrolling amount have to floating-point pipeline depths?

Got questions? Get instant answers now!

On a processor that can execute one floating-point multiply, one floating-point addition/subtraction, and one memory reference per cycle, what’s the best performance you could expect from the following loop?


DO I = 1,10000 A(I) = B(I) * C(I) - D(I) * E(I)ENDDO
Got questions? Get instant answers now!

Try unrolling, interchanging, or blocking the loop in subroutine BAZFAZ to increase the performance. What method or combination of methods works best? Look at the assembly language created by the compiler to see what its approach is at the highest level of optimization.

Compile the main routine and BAZFAZ separately; adjust NTIMES so that the untuned run takes about one minute; and use the compiler’s default optimization level.


PROGRAM MAIN IMPLICIT NONEINTEGER M,N,I,J PARAMETER (N = 512, M = 640, NTIMES = 500)DOUBLE PRECISION Q(N,M), R(M,N) CDO I=1,M DO J=1,NQ(J,I) = 1.0D0 R(I,J) = 1.0D0ENDDO ENDDOC DO I=1,NTIMESCALL BAZFAZ (Q,R,N,M) ENDDOENDSUBROUTINE BAZFAZ (Q,R,N,M) IMPLICIT NONEINTEGER M,N,I,J DOUBLE PRECISION Q(N,M), R(N,M)C DO I=1,NDO J=1,M R(I,J) = Q(I,J) * R(J,I)ENDDO ENDDOC END
Got questions? Get instant answers now!

Code the matrix multiplication algorithm in the “straightforward” manner and compile it with various optimization levels. See if the compiler performs any type of loop interchange.

Try the same experiment with the following code:


DO I=1,N DO J=1,NA(I,J) = A(I,J) + 1.3 ENDDOENDDO

Do you see a difference in the compiler’s ability to optimize these two loops? If you see a difference, explain it.

Got questions? Get instant answers now!

Code the matrix multiplication algorithm both the ways shown in this chapter. Execute the program for a range of values for N. Graph the execution time divided by N3 for values of N ranging from 50×50 to 500×500. Explain the performance you see.

Got questions? Get instant answers now!

Get Jobilize Job Search Mobile App in your pocket Now!

Get it on Google Play Download on the App Store Now




Source:  OpenStax, High performance computing. OpenStax CNX. Aug 25, 2010 Download for free at http://cnx.org/content/col11136/1.5
Google Play and the Google Play logo are trademarks of Google Inc.

Notification Switch

Would you like to follow the 'High performance computing' conversation and receive update notifications?

Ask