This change adds the option to use the memcheck with random memory
hierarchies at the moment limited to a maximum depth of 3 allowing
testing with uncommon topologies.
Change-Id: Id2c2fe82a8175d9a67eb4cd7f3d2e2720a809b60
Reviewed-by: Andreas Hansson <andreas.hansson@arm.com>
If the cache access mode is parallel, i.e. "sequential_access" parameter
is set to "False", tags and data are accessed in parallel. Therefore,
the hit_latency is the maximum latency between tag_latency and
data_latency. On the other hand, if the cache access mode is
sequential, i.e. "sequential_access" parameter is set to "True",
tags and data are accessed sequentially. Therefore, the hit_latency
is the sum of tag_latency plus data_latency.
Signed-off-by: Jason Lowe-Power <jason@lowepower.com>
Open up for other subclasses to BaseCache and transition to using the
explicit Cache subclass.
--HG--
rename : src/mem/cache/BaseCache.py => src/mem/cache/Cache.py
This patch takes the final step in removing the is_top_level parameter
from the cache. With the recent changes to read requests and write
invalidations, the parameter is no longer needed, and consequently
removed.
This also means that asymmetric cache hierarchies are now fully
supported (and we are actually using them already with L1 caches, but
no table-walker caches, connected to a shared L2).
This patch introduces a few subclasses to the CoherentXBar and
NoncoherentXBar to distinguish the different uses in the system. We
use the crossbar in a wide range of places: interfacing cores to the
L2, as a system interconnect, connecting I/O and peripherals,
etc. Needless to say, these crossbars have very different performance,
and the clock frequency alone is not enough to distinguish these
scenarios.
Instead of trying to capture every possible case, this patch
introduces dedicated subclasses for the three primary use-cases:
L2XBar, SystemXBar and IOXbar. More can be added if needed, and the
defaults can be overridden.
This is a rather unfortunate copy of the memtest.py example script,
that actually stresses the system with true sharing as opposed to the
false sharing of the MemTest. To do so it uses TrafficGen instances to
generate the reads/writes, and MemCheckerMonitor combined with the
MemChecker to check the validity of the read/written values.
As a bonus, this script also enables the addition of prefetchers, and
the traffic is created to have a mix of random addresses and linear
strides. We use the TaggedPrefetcher since the packets do not have a
request with a PC.
At the moment the code is almost identical to the memtest.py script,
and no effort has been made to factor out the construction of the
tree. The challenge is that the instantiation and connection of the
testers and monitors is done as part of the tree building.
