cc-metric-collector/collectors/likwid/groups/zen2/CACHE.txt

SHORT Data cache miss rate/ratio

EVENTSET
FIXC1 ACTUAL_CPU_CLOCK
FIXC2 MAX_CPU_CLOCK
PMC0  RETIRED_INSTRUCTIONS
PMC1  CPU_CLOCKS_UNHALTED
PMC2  DATA_CACHE_ACCESSES
PMC3  DATA_CACHE_REFILLS_ALL

METRICS
Runtime (RDTSC) [s] time
Runtime unhalted [s]   FIXC1*inverseClock
Clock [MHz]  1.E-06*(FIXC1/FIXC2)/inverseClock
CPI   PMC1/PMC0
data cache requests PMC2
data cache request rate PMC2/PMC0
data cache misses PMC3
data cache miss rate PMC3/PMC0
data cache miss ratio PMC3/PMC2

LONG
Formulas:
data cache requests = DATA_CACHE_ACCESSES
data cache request rate = DATA_CACHE_ACCESSES / RETIRED_INSTRUCTIONS
data cache misses = DATA_CACHE_REFILLS_ALL
data cache miss rate = DATA_CACHE_REFILLS_ALL / RETIRED_INSTRUCTIONS
data cache miss ratio = DATA_CACHE_REFILLS_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.