Copyright by William Lloyd Bircher 2010 - The Laboratory for ...
Copyright by William Lloyd Bircher 2010 - The Laboratory for ...
Copyright by William Lloyd Bircher 2010 - The Laboratory for ...
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Watts<br />
90<br />
80<br />
70<br />
60<br />
50<br />
40<br />
30<br />
20<br />
10<br />
0<br />
DIMM<br />
CPU<br />
10 17 25 18 10 9 16 16 14 21 12 22 26 29 25 25 25 25 34 34 36 29 38 32 38 33 35 34 36 39<br />
50 49 49 48 48 48 47 46 46 46 45 45 43 42 42 42 41 40 40 40 39 39 38 37 37 35 35 35 34 34<br />
gamess<br />
h264ref<br />
hmmer<br />
calculix<br />
namd<br />
povray<br />
gromacs<br />
perlbench<br />
gobmk<br />
dealII<br />
sjeng<br />
tonto<br />
xalancbmk<br />
cactusADM<br />
bzip2<br />
Average<br />
astar<br />
gcc<br />
sphinx3<br />
wrf<br />
bwaves<br />
zeusmp<br />
leslie3d<br />
omnetpp<br />
GemsFDTD<br />
soplex<br />
mcf<br />
libquantum<br />
milc<br />
lbm<br />
Figure 4.4 SPEC CPU2006 Average Core vs. DIMM Power<br />
4.1.3 Desktop Plat<strong>for</strong>m – SYSmark 2007<br />
In this section average power consumption levels across a range of workloads are<br />
considered. Two major conclusions <strong>for</strong> desktop workloads are drawn: the core is the<br />
largest power consumer and it contains the most variability across workloads. Though<br />
other subsystems, such as memory controller and DIMM, have significant variability<br />
within workloads, only the core demonstrates significant variability in average power<br />
across desktop workloads. Consider Figure 4.5: while average core power varies <strong>by</strong> as<br />
much as 57 percent, the next most variable subsystem, DIMM, varies <strong>by</strong> only 17 percent.<br />
Note, this conclusion does not hold <strong>for</strong> server systems and workloads in which much<br />
larger installations of memory modules cause greater variability in power consumption.<br />
<strong>The</strong> cause of this core power variation can be attributed to a combination of variable<br />
levels of thread-level parallelism and core-level power adaptations. In the case of 3D, the<br />
workload is able to consistently utilize multiple cores.<br />
48