Affiliations: VLSI Design Center – Democritus Univ. Thrace,
67100 Xanthi, Greece | DACYA/UCM, Avda. Complutense s/n, 28040 Madrid,
Spain | IMEC vzw, Kapeldreef 75, 3001 Heverlee, Belgium | Professor at Katholieke Universiteit Leuven,
Belgium | Microprocessors and Digital Systems Lab, School of
Electrical and Computer Engineering, National Technical University of Athens,
15780 Zografou, Greece
Abstract: Today, wireless networks are becoming increasingly ubiquitous.
Usually several complex multi-threaded applications are mapped on a single
embedded system and each of them is triggered by a different input stream (in
accordance with the run-time behaviours of the user and the environment). This
dynamicity renders the task of fully analyzing at design-time these systems
very complex, if not impossible. Therefore, run-time information has to be used
in order to produce an efficient design. This introduces new challenges,
especially for embedded system designers using a Direct Memory Access (DMA)
module, who have to know in advance the memory transfer behaviour of the whole
system, in order to design and program their DMA efficiently. This is
especially important in embedded systems with DRAM memories as the concurrent
accesses from different processing elements can adversely affect the page-based
architecture of these memory elements. Even more, the increasingly common usage
of dynamic data types further complicates the problem because the exact
location of data instances in the memory is unknown at design-time. In this
paper we propose a system-level optimization methodology to adapt the DMA usage
parameters automatically at run-time, according to online information. With our
proposed optimization approach we manage to reduce the mean latency of the
memory transfers by more than 18%, thus reducing the average number of cycles
that processing elements or DMAs have to waste waiting for data from the main
memory, while optimizing energy consumption and system responsiveness. We
evaluate our approach using a set of real-life applications and real wireless
dynamic streams.