The high performance Digital Signal Processors (DSPs) currently manufactured by Texas Instruments are heterogeneous multiprocessor architectures. Programming these architectures is a complex task often reserved to specialized engineers because the bottlenecks of both the algorithm and the architecture need to be deeply understood in order to obtain a fairly parallel execution. The PREESM framework objective is to simplify the programming of multicore DSP systems by building on dataflow programming methods. The current functionalities of this scalable framework cover memory and time analysis, as well as automatic deadlock-free code generation. Several tutorials are provided with the tool for fast initiation of C programmers to multicore DSP programming. This paper demonstrates PREESM capabilities by comparing simulation and execution performances on a stereo matching algorithm prototyped on the TMS320C6678 8-core DSP device.

International audience—Dataflow models of computation are widely used for the specification, analysis, and optimization of Digital Signal Processing (DSP) applications. In this paper a new meta-model called PiMM is introduced to address the important challenge of managing dynamics in DSP-oriented representations. PiMM extends a dataflow model by introducing an explicit parameter dependency tree and an interface-based hierarchical compositionality mechanism. PiMM favors the design of highly-efficient heterogeneous multicore systems, specifying algorithms with customizable trade-offs among predictability and exploita-tion of both static and adaptive task, data and pipeline paral-lelism. PiMM fosters design space exploration and reconfigurable resource allocation in a flexible dynamic dataflow context

A high pressure is put on mobile devices to support increasingly advanced applications requiring more processing capabilities. Among those, the emerging High Efficiency Video Coding (HEVC) provides a better video quality for the same bit rate than the previous H.264 standard. A limitation in the usability of a mobile video playing device is the lack of support for guaranteeing stand-by time and up time for battery driven devices. The Green Metadata initiative within the MPEG standard was launched to address the power saving issues of the decoder and defines the technology requirements. In this paper, we propose a HEVC decoder with tunable decoding quality levels for maximum power savings as suggested in the scope of the Green Metadata initiative. Our experiments reveal that the modified HEVC video decoder can save up to 28 % of power consumption in real-world platforms while keeping better quality than decoding with H.264.