1.12 Section 1.10 cites as a pitfall the utilization of a subset of the performance

equation as a performance metric. To illustrate this, consider the following two

processors. P1 has a clock rate of 4 GHz, average CPI of 0.9, and requires the

execution of 5.0E9 instructions. P2 has a clock rate of 3 GHz, an average CPI of

0.75, and requires the execution of 1.0E9 instructions. 1.12.1 [5] <1.6, 1.10> One usual fallacy is to consider the computer with the

largest clock rate as having the largest performance. Check if this is true for P1 and

1.12.2 [10] <1.6, 1.10> Another fallacy is to consider that the processor executing

the largest number of instructions will need a larger CPU time. Considering that

processor P1 is executing a sequence of 1.0E9 instructions and that the CPI of

processors P1 and P2 do not change, determine the number of instructions that P2

can execute in the same time that P1 needs to execute 1.0E9 instructions.

1.12.3 [10] <1.6, 1.10> A common fallacy is to use MIPS (millions of

instructions per second) to compare the performance of two different processors,

and consider that the processor with the largest MIPS has the largest performance.

Check if this is true for P1 and P2.

1.12.4 [10] <1.10> Another common performance figure is MFLOPS (millions

of floating-point operations per second), defined as

MFLOPS = No. FP operations / (execution time 1E6)

but this figure has the same problems as MIPS. Assume that 40% of the instructions

executed on both P1 and P2 are floating-point instructions. Find the MFLOPS

figures for the programs.