This patch adds two additional scheduling constraints to the DRAM
controller model, to constrain the activation rate. The two metrics
are determine the size of the activation window in terms of the number
of activates and the minimum time required for that number of
activates. This maps to current DDRx, LPDDRx and WIOx standards that
have either tFAW (4 activate window) or tTAW (2 activate window)
scheduling constraints.
When casting objects in the generated SWIG interfaces, SWIG uses
classical C-style casts ( (Foo *)bar; ). In some cases, this can
degenerate into the equivalent of a reinterpret_cast (mainly if only a
forward declaration of the type is available). This usually works for
most compilers, but it is known to break if multiple inheritance is
used anywhere in the object hierarchy.
This patch introduces the cxx_header attribute to Python SimObject
definitions, which should be used to specify a header to include in
the SWIG interface. The header should include the declaration of the
wrapped object. We currently don't enforce header the use of the
header attribute, but a warning will be generated for objects that do
not use it.
This patch introduces a high-level model of a DRAM controller, with a
basic read/write buffer structure, a selectable and customisable
arbiter, a few address mapping options, and the basic DRAM timing
constraints. The parameters make it possible to turn this model into
any desired DDRx/LPDDRx/WideIOx memory controller.
The intention is not to be cycle accurate or capture every aspect of a
DDR DRAM interface, but rather to enable exploring of the high-level
knobs with a good simulation speed. Thus, contrary to e.g. DRAMSim
this module emphasizes simulation speed with a good-enough accuracy.
This module is merely a starting point, and there are plenty additions
and improvements to come. A notable addition is the support for
address-striping in the bus to enable a multi-channel DRAM
controller. Also note that there are still a few "todo's" in the code
base that will be addressed as we go along.
A follow-up patch will add basic performance regressions that use the
traffic generator to exercise a few well-defined corner cases.
