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In this exercise, we look at how software techniques can extract instruction-level parallelism (ILP) in a common vector loop. The following loop is the so-called DAXPY loop (double-precision aX plus Y) and is the central operation in Gaussian elimination. The following code implements the DAXPY operation, Y = aX + Y, for a vector length 100. Initially, F0 holds constant a, R1 is set to the base address of array X, and R2 is set to the base address of array Y: DADDIU R4, R1, #800 ; R4 = upper bound for X foo: L. D F2, 0(R1) ; load X(i) to F2 MUL. D F4, F2, F0 ; (F4) = a*X(i) L. D F6, 0(R2) ; (F6) = Y(i) ADD. D F6, F4, F6 ; (F6) = a*X(i) + Y(i) S. D F6, 0(R2) ; store F6 to Y(i) DADDIU R1, R1, #8 ; increase X index DADDIU R2, R2, #8 ; increase Y index DSLTU R3, R1, R4 ; test: continue loop? BNEZ R3, foo ; loop if needed

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In this exercise, we look at how software techniques can extract instruction-level parallelism (ILP)...

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