Embedded multimedia devices are now a common element of our environment, such as mp3 players, handheld devices, and so on. Choosing the right main processing element is a key issue for the success of these devices, and their consumption, performance, retargetability, and development time are some of the elements that need to be analyzed and well-balanced. In this paper, we map the same multimedia application (MPEG-4 main profile) into various target platforms generally used in the embedded area. The design flow of our work starts with a single MPEG-4 encoder description which is later refined and optimized to be implemented on different platforms: an embedded platform formed by a high performance digital signal processor and an embedded processor, an application specific instruction processor, a specific hardware implemented in a field-programmable gate array for accelerating the data-flow part of the system with a soft-core for the control part, and an application specific integrated circuit. The main contribution of this paper is to illustrate a methodology that can be generalized to different data dominant applications. This paper describes a new methodology to obtain near optimal implementation from concept to silicon for all platforms and it can be extended to any hybrid HW/SW multimedia platform. We evaluate the different transformations of each platform to arrive at an optimal implementation. These higher level transformations allow achieving better results than using more precise efforts in mapping the design in the physical level. This methodology can be extended to any data dominant application.

Traditionally, engineers design for the worst case scenario but in most cases the maximum performance is not required so that there is an important waste of energy consumption. Developers should design systems for different power consumption versus execution time tradeoffs. By exploiting Dynamic Voltage and Frequency Scaling (DVFS) techniques we can reach different computational/power trades offs points and thus design power efficient platforms. In this paper, we present a high level methodology to get an optimal set of working points for an MPEG-4 Single Profile (SP) Video encoder implementation. The flow starts from a C++ description of a MPEG-4 encoder which is translated to a SystemC implementation which will be analyzed and further mapped into different platforms. Refined code is migrated to four different processor architectures: a processor research framework (trimaran), a soft core processor with specific functional units implemented on an Altera FPGA, an ASIC and a typical DSP.

Users expect future handheld devices to provide extended multimedia functionality and have long battery life. This type of application imposes heavy constraints on performance and power consumption and forces designers to optimize all parts of their platform. Evaluating the overall platform power breakdown is therefore critical to determine where to spend the efforts on power optimization. Surprisingly, few studies exist on that topic and decisions generally rely on common belief. We have realized a complete power breakdown for a realistic platform to identify the major power bottlenecks. This paper presents this power assessment of a realistic heterogeneous network on chip platform including processors, network and data/instruction memory hierarchy, running a video processing chain from camera to display. Our power breakdown identifies the main bottlenecks in the memory hierarchy and the foreground memory, and shows that global interconnect is not that critical for a well-optimized application mapping.

Users expect future handheld devices to provide extended multimedia functionality and have long battery life. This type of application imposes heavy constraints on both (realtime) performance and energy consumption and forces designers to optimise all parts of their platform. In this experiment we focus on the different processor core design options for embedded platforms, including the effect of instruction memory hierarchy on the energy consumption. The results show that significant improvements for energy efficiency and/or performance over currently used RISC or VLIW processors can be achieved. We conclude, based on concrete data for a realistic application, that different styles, including both configurable hardware and instruction set processors, find their way into heterogeneous platforms and designers need to be aware of the trade-offs. Secondly, we show for the same application task that a heavily optimised instruction/configuration memory hierarchy can significantly reduce the energy consumption of this part, so it forms a crucial part of every energy aware design.