cc-metric-collector/collectors/likwid/groups/k10/CACHE.txt

SHORT Data cache miss rate/ratio

EVENTSET
PMC0  INSTRUCTIONS_RETIRED
PMC1  DATA_CACHE_ACCESSES
PMC2  DATA_CACHE_REFILLS_L2_ALL
PMC3  DATA_CACHE_REFILLS_NORTHBRIDGE_ALL

METRICS
Runtime (RDTSC) [s] time
data cache misses PMC2+PMC3
data cache request rate PMC1/PMC0
data cache miss rate (PMC2+PMC3)/PMC0
data cache miss ratio (PMC2+PMC3)/PMC1

LONG
Formulas:
data cache misses = DATA_CACHE_REFILLS_L2_AL + DATA_CACHE_REFILLS_NORTHBRIDGE_ALL
data cache request rate = DATA_CACHE_ACCESSES / INSTRUCTIONS_RETIRED
data cache miss rate = (DATA_CACHE_REFILLS_L2_AL + DATA_CACHE_REFILLS_NORTHBRIDGE_ALL)/INSTRUCTIONS_RETIRED
data cache miss ratio = (DATA_CACHE_REFILLS_L2_AL + DATA_CACHE_REFILLS_NORTHBRIDGE_ALL)/DATA_CACHE_ACCESSES
-
This group measures the locality of your data accesses with regard to the
L1 cache. Data cache request rate tells you how data intensive your code is
or how many data accesses you have on average per instruction.
The data cache miss rate gives a measure how often it was necessary to get
cache lines from higher levels of the memory hierarchy. And finally
data cache miss ratio tells you how many of your memory references required
a cache line to be loaded from a higher level. While the# data cache miss rate
might be given by your algorithm you should try to get data cache miss ratio
as low as possible by increasing your cache reuse.
This group was taken from the whitepaper -Basic Performance Measurements for AMD Athlon 64,
AMD Opteron and AMD Phenom Processors- from Paul J. Drongowski.