快速、高效和可预见的记忆体存取

The influence of embedded systems is constantly growing. Increasingly powerful
and versatile devices are being developed and put on the market at a fast
pace. The number of features is increasing, and so are the constraints on
the systems concerning size, performance, energy dissipation and timing predictability.
Since most systems today use a processor to execute an application
program rather than using dedicated hardware, the requirements can not be
fulfilled by hardware architects alone: Hardware and software have to work
together in order to meet the tight constraints put on modern devices. This
work presents approaches that target the software generation process using an
energy and memory architecture aware C-compiler. The consideration of energy
dissipation and of the memory architecture leads to a large optimization
potential concerning performance and energy dissipation.
This work first presents an overview over the used timing, energy and
simulation models for one processor architecture and for different memory
architectures like caches, scratchpad memories and main memories in both
SRAM, DRAM and Flash technology. Following an introduction to the used
compilation framework, the compiler based exploitation of partitioned scratchpad
memories is presented. A simple formalized Base model is presented that
models the consequences of statically allocating instructions and data to several
small scratchpad partitions, followed by a number of extensions that treat
memory objects and their dependencies at a finer granularity. A method for
allocating objects to separate scratchpad memories for instructions and data,
as found in the most recent ARM designs, is also presented. Finally, a model
that also considers the leakage power of memories is introduced. Results show
that significant savings of up to 80% of the total energy can be achieved
by using the presented scratchpad allocation algorithms. The flexibility and
extensibility of the presented approaches is another benefit.
Many embedded systems have to respect timing constraints. Therefore,
timing predictability is of increasing importance. Whenever guarantees concerning
reaction times have to be given, worst case execution time (WCET)
analysis techniques are being used during the design of the system in order