Digital signal processing applications are specified with floating-point data types but they are usually implemented in embedded systems with fixed-point arithmetic to minimise cost and power consumption. Thus, methodologies which establish automatically the fixed-point specification are required to reduce the application time-to-market. In this paper, a new methodology for the floating-to-fixed point conversion is proposed for software implementations. The aim of our approach is to determine the fixed-point specification which minimises the code execution time for a given accuracy constraint. Compared to previous methodologies, our approach takes into account the DSP architecture to optimise the fixed-point formats and the floating-to-fixed-point conversion process is coupled with the code generation process. The fixed-point data types and the position of the scaling operations are optimised to reduce the code execution time. To evaluate the fixed-point computation accuracy, an analytical approach is used to reduce the optimisation time compared to the existing methods based on simulation. The methodology stages are described and several experiment results are presented to underline the efficiency of this approach.

The energy consumption of manycore is dominated by data movement, which calls for energy-efficient and high-bandwidth interconnects. Integrated optics is promising technology to overcome the bandwidth limitations of electrical interconnects. However, it suffers from high power overhead related to low efficiency lasers, which calls for the use of approximate communications for error tolerant applications. In this context, this paper investigates the design of an Optical NoC supporting the transmission of approximate data. For this purpose, the least significant bits of floating point numbers are transmitted with low power optical signals. A transmission model allows estimating the laser power according to the targeted BER and a micro-architecture allows configuring, at run-time, the number of approximated bits and the laser output powers. Simulations results show that, compared to an interconnect involving only robust communications, approximations in the optical transmission lead to up to 42% laser power reduction for image processing application with a limited degradation at the application level.

This paper deals with the real-time scheduling in a reconfigurable multi-core platform powered by a rechargeable battery. A reconfiguration scenario is defined as an operation that allows the addition-removal-modification of tasks which may result in timing unfeasibility. Such a system may face several scenarios: i) increased power consumption that, in the worst case, may surpass the available energy budget, ii) increased computing demand, which may lead to the violation of real-time constraints, and iii) increased memory demand, potentially exceeding the provided memory capacity. To prevent these problems during the execution, a new scheduling strategy is necessary. The proposal is based on the assignment of tasks to different processor cores to satisfy these constraints simultaneously after any reconfiguration scenario. The effectiveness and performance of the designed approach are evaluated through simulation studies. An intelligent tool named Reconf-Pack is developed in our research laboratory to support this new proposed approach and to simulate it over randomly generated tasks.