CROSS-LAYER CUSTOMIZATION FOR LOW POWER AND HIGH PERFORMANCE EMBEDDED MULTI-CORE PROCESSORS

Due to physical limitations and design difficulties, computer processor architecture has shifted to multi-core and even many-core based approaches in recent years. Such architectures provide potentials for sustainable performance scaling into future peta-scale/exa-scale computing platforms, at affordable power budget, design complexity, and verification efforts. To date, multi-core processor products have been replacing uni-core processors in almost every market segment, including embedded systems, general-purpose desktops and laptops, and super computers. However, many issues still remain with multi-core processor architectures that need to be addressed before their potentials could be fully realized. People in both academia and industry research community are still seeking proper ways to make efficient and effective use of these processors. The issues involve hardware architecture trade-offs, the system software service, the run-time management, and user application design, which demand more research effort into this field. Due to the architectural specialties with multi-core based computers, a Cross-Layer Customization framework is proposed in this work, which combines application specific information and system platform features, along with necessary operating system service support, to achieve exceptional power and performance efficiency for targeted multi-core platforms. Several topics are covered with specific optimization goals, including snoop cache coherence protocol, inter-core communication for producer-consumer applications, synchronization mechanisms, and off-chip memory bandwidth limitations. Analysis of benchmark program execution with conventional mechanisms is made to reveal the overheads in terms of power and performance. Specific customizations are proposed to eliminate such overheads with support from hardware, system software, compiler, and user applications. Experiments show significant improvement on system performance and power efficiency

Lightweight Multitasking Support for Embedded Systems using the Phantom Serializing Compiler

Embedded software continues to play an ever increasing role in the design of complex embedded applications. In part, the elevated level of abstraction provided by a high-level programming paradigm immensely facilitates a short design cycle, fewer errors, portability, and reuse. Serializing compilers have been proposed as an alternative to traditional OS techniques, enabling a designer to develop multitasking applications without the need of OS support. In this work, we outline the inner workings of the Phantom serializing compiler and analyze the quality of the generated code with respect to memory and processing overheads. Our results show that such serializing compilers are extremely efficient, making them ideal to be used in design of highly parallel applications (e.g., multimedia, graphics, and signal processing applications)