Performance analysis of a hardware accelerator of dependence management for taskbased dataflow programming models

Along with the popularity of multicore and manycore, task-based dataflow programming models obtain great attention for being able to extract high parallelism from applications without exposing the complexity to programmers. One of these pioneers is the OpenMP Superscalar (OmpSs). By implementing dynamic task dependence analysis, dataflow scheduling and out-of-order execution in runtime, OmpSs achieves high performance using coarse and medium granularity tasks. In theory, for the same application, the more parallel tasks can be exposed, the higher possible speedup can be achieved. Yet this factor is limited by task granularity, up to a point where the runtime overhead outweighs the performance increase and slows down the application. To overcome this handicap, Picos was proposed to support task-based dataflow programming models like OmpSs as a fast hardware accelerator for fine-grained task and dependence management, and a simulator was developed to perform design space exploration. This paper presents the very first functional hardware prototype inspired by Picos. An embedded system based on a Zynq 7000 All-Programmable SoC is developed to study its capabilities and possible bottlenecks. Initial scalability and hardware consumption studies of different Picos designs are performed to find the one with the highest performance and lowest hardware cost. A further thorough performance study is employed on both the prototype with the most balanced configuration and the OmpSs software-only alternative. Results show that our OmpSs runtime hardware support significantly outperforms the software-only implementation currently available in the runtime system for finegrained tasks.This work is supported by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology through TIN2015-65316-P project, by the Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272) and by the European Research Council RoMoL Grant Agreement number 321253. We also thank the Xilinx University Program for its hardware and software donations.Peer ReviewedPostprint (published version

A Virtual Testbed for Embedded Systems

Hardware-In-the-Loop (HIL) Simulation is a simulation approach in which a hardware embedded processor is connected to the simulation computer that simulates the electrical/mechanical devices controlled by the embedded processor. By using a real-time simulation computer and special-purpose hardware for connecting to the embedded processor, this method of simulation can be very precise but is costly. We are proposing an alternative method, HIL simulation with a network link, in which the device under test (the embedded processor) communicates with the simulation computer over a network connection (in our case a serial line) instead of through special-purpose hardware. We present an abstraction layer that facilitates the simulation of external devices. An earlier prototype had been developed for a 16-bit TMS320LF2407A DSP from Texas Instruments. We generalized the approach to the more advanced 32-bit TMS320F28335 DSP. We have made the changes in the DSP abstraction layer to enable more features and provide more flexibility to the programmer. For example, we introduced a shadow interrupt vector to make the simulation layer more general. We developed various scenarios to measure the performance of the system. In particular, we measure round-trip time and through-put for the communication between the simulator and the DSP. Also we rewrote the serial line drivers on the DSP to incorporate different working scenarios and to invoke the timers on the DSP for measuring the execution time. Our work helps to judge the performance of the system and to identify the application domains for this approach

SHINe: Simulator for satellite on-board high-speed networks featuring SpaceFibre and SpaceWire protocols

The continuous innovation of satellite payloads is leading to an increasing demand of data-rate for on-board satellite networks. In particular, modern optical detectors generate and need to transfer data at more than 1 Gbps, a speed that cannot be satisfied with standardized technologies such as SpaceWire. To fill this gap, the European Space Agency (ESA) is supporting the development of a new high-speed link standard, SpaceFibre. SpaceFibre provides a data-rate higher than 6.25 Gbps, together with the possibility to use multiple Virtual Channels running over the same physical link, each one configurable with flexible Quality of Service parameters. These features make a SpaceFibre network very appealing but also complex to set up in order to achieve the desired end-to-end requirements. To help this process, a Simulator for HIgh-speed Network (SHINe) based on the open-source toolkit OMNeT++ has been developed and is presented in this paper. It supports the simulation of SpaceFibre and SpaceWire protocols in order to help both the final steps of the standardization process and the system engineers in the setup and test of new networks. SHINe allows to precisely simulate common network metrics, such as latency and bandwidth usage, and it can be connected to real hardware in a Hardware-in-the-Loop configuration

Physical Interaction and Control of Robotic Systems Using Hardware-in-the-Loop Simulation

Robotic systems used in industries and other complex applications need huge investment, and testing of them under robust conditions are highly challenging. Controlling and testing of such systems can be done with ease with the support of hardware-in-the-loop (HIL) simulation technique and it saves lot of time and resources. The chapter deals on the various interaction methods of robotic systems with physical environments using tactile, force, and vision sensors. It also discusses about the usage of hardware-in-the-loop technique for testing of grasp and task control algorithms in the model of robotic systems. The chapter also elaborates on usage of hardware and software platforms for implementing the control algorithms for performing physical interaction. Finally, the chapter summarizes with the case study of HIL implementation of the control algorithms in Texas Instruments (TI) C2000 microcontroller, interacting with model of Kuka’s youBot Mobile Manipulator. The mathematical model is developed using MATLAB software and the virtual animation setup of the robot is developed using the Virtual Robot Experimentation Platform (V-REP) robot simulator. By actuating the Kuka’s youBot mobile manipulator in the V-REP tool, it is observed to produce a tracking accuracy of 92% for physical interaction and object handling tasks