Difference between revisions of "ExcessDataVolume"
Jump to navigation
Jump to search
m |
|||
| Line 1: | Line 1: | ||
| + | [[Category:Performance Pattern]] | ||
== Description == | == Description == | ||
The pattern "Excess data volume" describes the performance issue that you get, when data is not fitting into intended memory. An example is the block size for spatial blocking which need to be adjusted based on the cache size. If you excess the size of the cache size, the data needs to be fetched from a lower cache level with higher access times. | The pattern "Excess data volume" describes the performance issue that you get, when data is not fitting into intended memory. An example is the block size for spatial blocking which need to be adjusted based on the cache size. If you excess the size of the cache size, the data needs to be fetched from a lower cache level with higher access times. | ||
Latest revision as of 16:18, 3 September 2019
Description
The pattern "Excess data volume" describes the performance issue that you get, when data is not fitting into intended memory. An example is the block size for spatial blocking which need to be adjusted based on the cache size. If you excess the size of the cache size, the data needs to be fetched from a lower cache level with higher access times.
Symptoms
A simple bandwidth model is too optimistic.
Detection
- Low utilization of the available bandwidth (in order to get reference bandwidth, see Bandwidth saturation pattern
- Low cache hit ratio
- Frequent CL evicts or replacements
Recommended LIKWID groups: CACHE, DATA and MEM
Possible optimizations and/or fixes
Reduce the data that should reside in memory/cache
Applicable applications or algorithms or kernels
- All spatially blocked kernels