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Fast, Efficient and Predictable Memory Accesses: Optimization Algorithms for Memory Architecture Aware Compilation

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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.
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