Evaluating Rapid Application Development with Python for Heterogeneous Processor-based FPGAs

As modern FPGAs evolve to include more het- erogeneous processing elements, such as ARM cores, it makes sense to consider these devices as processors first and FPGA accelerators second. As such, the conventional FPGA develop- ment environment must also adapt to support more software- like programming functionality. While high-level synthesis tools can help reduce FPGA development time, there still remains a large expertise gap in order to realize highly performing implementations. At a system-level the skill set necessary to integrate multiple custom IP hardware cores, interconnects, memory interfaces, and now heterogeneous processing elements is complex. Rather than drive FPGA development from the hardware up, we consider the impact of leveraging Python to ac- celerate application development. Python offers highly optimized libraries from an incredibly large developer community, yet is limited to the performance of the hardware system. In this work we evaluate the impact of using PYNQ, a Python development environment for application development on the Xilinx Zynq devices, the performance implications, and bottlenecks associated with it. We compare our results against existing C-based and hand-coded implementations to better understand if Python can be the glue that binds together software and hardware developers.Comment: To appear in 2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM'17

M-Fly AUVSI-SUAS Autonomous Unmanned Vehicle Hardware System

The M-Fly student project team is a multidisciplinary organization whose mission is to design, build, and compete aircraft. M-Fly builds several planes from scratch each year which are submitted to multiple competitions. One of these planes, the Michigan Autonomous (MAT) system, is an autonomous, unmanned system which is submitted to the Association for Unmanned Vehicle Systems International – Student Unmanned Aerial Systems (AUVSI-SUAS) competition. The yearly competition specification outlines several mission goals that M-Fly’s MAT system must attempt. Among these for the 2020 competition were autonomous flight; object detection, localization, and classification (ODLC) with imaging; autonomous waypoint navigation; and autonomous detection and avoidance of other aircraft. In 2020, the competition also specified an additional mission goal involving a payload drop of an autonomous ground vehicle that had even more tasks itself. Though still a new competition and system for M-Fly, the third iteration of the MAT platform, the MAT-3, presented a novel design based on the lessons learned from the first two iterations. This report details the design of the system electronics architecture, evaluates the success of the system, and makes recommendations for further tests and development.http://deepblue.lib.umich.edu/bitstream/2027.42/167247/1/HonorsCapstoneFinalReport-Matthew_French.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167247/2/HonorsCapstoneFinalPresentation-Matthew_French.pd

Proceedings of the University of Cambridge Interdisciplinary Graduate Conference 2010

Second, revised edition of the Proceedings, originally published on CD-Rom as ISBN 978-0-9566139-0-5.Proceedings of the third annual Interdisciplinary Graduate Conference at the University of Cambridge

Exploring coherence and disorder: an analysis of spatial patterning within the neuromesodermal progenitor niche

How regulatory frameworks control cellular identity and organisation via cell-cell communication is a poorly understood yet fundamental process in development. Different signalling pathway regulatory mechanisms can create a variety of spatial patterns of transcription factor (TF) expression and differentiation, however quantitatively assessing multicellular organisation in 3D has only recently been made possible due to advances in imaging and image analysis tools. Downstream analysis methods are still in their infancy and require further development to utilise the newly available information. Neuromesodermal progenitors (NMPs) are a bipotent population of cells in the post gastrulation epiblast that self-renew while allocating cells to neural and mesodermal tissues of the trunk. Gradients of Retinoic acid, Wnt, and FGF signalling direct the neural vs mesoderm cell fate decision and regionalise the axial progenitor niches, but the spatial patterning of TF expression has not been quantified. Further, previous work shows that the Notch signalling pathway also regulates the cell fate decision in NMPs, but this is not well characterised and it’s unknown if Notch contributes to any TF patterning. I aimed to use systems biology inspired analysis methods to investigate the role of Notch signalling in NMP fate and patterning. First, I investigated the pro-neural effect of Notch inhibition in NMPs and identified which Notch components are expressed. Then, I developed quantitative analysis methods that show differential spatial patterning of key TF fate markers in NMP niches in vitro and in vivo. Finally, I explored how Notch influences this patterning, overall providing a framework for future work to analyse spatial gene expression data

A Numerical Approach to Space-Time Finite Elements for the Wave Equation

We study a space-time finite element approach for the nonhomogeneous wave equation using a continuous time Galerkin method. We present fully implicit examples in 1+1, 2+1, and 3+1 dimensions using linear quadrilateral, hexahedral, and tesseractic elements. Krylov solvers with additive Schwarz preconditioning are used for solving the linear system. We introduce a time decomposition strategy in preconditioning which significantly improves performance when compared with unpreconditioned cases.Comment: 9 pages, 5 figures, 5 table