mirror of
https://github.com/ClusterCockpit/cc-metric-collector.git
synced 2024-09-20 15:37:27 +02:00
33 lines
1.2 KiB
Plaintext
33 lines
1.2 KiB
Plaintext
SHORT Data cache miss rate/ratio
|
|
|
|
EVENTSET
|
|
PMC0 RETIRED_INSTRUCTIONS
|
|
PMC1 DATA_CACHE_ACCESSES
|
|
PMC2 DATA_CACHE_REFILLS_VALID
|
|
PMC3 DATA_CACHE_MISSES_ALL
|
|
|
|
METRICS
|
|
Runtime (RDTSC) [s] time
|
|
data cache misses PMC3
|
|
data cache request rate PMC1/PMC0
|
|
data cache miss rate (PMC2)/PMC0
|
|
data cache miss ratio (PMC2)/PMC1
|
|
|
|
LONG
|
|
Formulas:
|
|
data cache misses = DATA_CACHE_MISSES_ALL
|
|
data cache request rate = DATA_CACHE_ACCESSES / RETIRED_INSTRUCTIONS
|
|
data cache miss rate = (DATA_CACHE_REFILLS_VALID) / RETIRED_INSTRUCTIONS
|
|
data cache miss ratio = (DATA_CACHE_REFILLS_VALID)/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.
|
|
|