Optimizing Scrubbing by Netlist Analysis for FPGA Configuration Bit Classification and Floorplanning

Existing scrubbing techniques for SEU mitigation on FPGAs do not guarantee an error-free operation after SEU recovering if the affected configuration bits do belong to feedback loops of the implemented circuits. In this paper, we a) provide a netlist-based circuit analysis technique to distinguish so-called critical configuration bits from essential bits in order to identify configuration bits which will need also state-restoring actions after a recovered SEU and which not. Furthermore, b) an alternative classification approach using fault injection is developed in order to compare both classification techniques. Moreover, c) we will propose a floorplanning approach for reducing the effective number of scrubbed frames and d), experimental results will give evidence that our optimization methodology not only allows to detect errors earlier but also to minimize the Mean-Time-To-Repair (MTTR) of a circuit considerably. In particular, we show that by using our approach, the MTTR for datapath-intensive circuits can be reduced by up to 48.5% in comparison to standard approaches

General purpose readout board {\pi} LUP: overview and results

This work gives an overview of the PCI-Express board $\pi$LUP, focusing on the motivation that led to its development, the technological choices adopted and its performance. The $\pi$LUP card was designed by INFN and University of Bologna as a readout interface candidate to be used after the Phase-II upgrade of the Pixel Detector of the ATLAS and CMS experiments at LHC. The same team in Bologna is also responsible for the design and commissioning of the ReadOut Driver (ROD) board - currently implemented in all the four layers of the ATLAS Pixel Detector (Insertable B-Layer, B-Layer, Layer-1 and Layer-2) - and acquired in the past years expertise on the ATLAS readout chain and the problematics arising in such experiments. Although the $\pi$LUP was designed to fulfill a specific task, it is highly versatile and might fit a wide variety of applications, some of which will be discussed in this work. Two 7$^{th}$-generation Xilinx FPGAs are mounted on the board: a Zynq-7 with an embedded dual core ARM Processor and a Kintex-7. The latter features sixteen 12.5$\,$Gbps transceivers, allowing the board to interface easily to any other electronic board, either electrically and/or optically, at the current bandwidth of the experiments for LHC. Many data-transmission protocols have been tested at different speeds, results will be discussed later in this work. Two batches of $\pi$LUP boards have been fabricated and tested, two boards in the first batch (version 1.0) and four boards in the second batch (version 1.1), encapsulating all the patches and improvements required by the first version.Comment: 6 pages, 10 figures, 21th Real Time Conference, winner of "2018 NPSS Student Paper Award Second Prize

LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft