Shifting capsule networks from the cloud to the deep edge

Capsule networks (CapsNets) are an emerging trend in image processing. In contrast to a convolutional neural network, CapsNets are not vulnerable to object deformation, as the relative spatial information of the objects is preserved across the network. However, their complexity is mainly related to the capsule structure and the dynamic routing mechanism, which makes it almost unreasonable to deploy a CapsNet, in its original form, in a resource-constrained device powered by a small microcontroller (MCU). In an era where intelligence is rapidly shifting from the cloud to the edge, this high complexity imposes serious challenges to the adoption of CapsNets at the very edge. To tackle this issue, we present an API for the execution of quantized CapsNets in Arm Cortex-M and RISC-V MCUs. Our software kernels extend the Arm CMSIS-NN and RISC-V PULP-NN to support capsule operations with 8-bit integers as operands. Along with it, we propose a framework to perform post-training quantization of a CapsNet. Results show a reduction in memory footprint of almost 75%, with accuracy loss ranging from 0.07% to 0.18%. In terms of throughput, our Arm Cortex-M API enables the execution of primary capsule and capsule layers with medium-sized kernels in just 119.94 and 90.60 milliseconds (ms), respectively (STM32H755ZIT6U, Cortex-M7 @ 480 MHz). For the GAP-8 SoC (RISC-V RV32IMCXpulp @ 170 MHz), the latency drops to 7.02 and 38.03 ms, respectively

Flexible multi-layer virtual machine design for virtual laboratory in distributed systems and grids.

We propose a flexible Multi-layer Virtual Machine (MVM) design intended to improve efficiencies in distributed and grid computing and to overcome the known current problems that exist within traditional virtual machine architectures and those used in distributed and grid systems. This thesis presents a novel approach to building a virtual laboratory to support e-science by adapting MVMs within the distributed systems and grids, thereby providing enhanced flexibility and reconfigurability by raising the level of abstraction. The MVM consists of three layers. They are OS-level VM, queue VMs, and components VMs. The group of MVMs provides the virtualized resources, virtualized networks, and reconfigurable components layer for virtual laboratories. We demonstrate how our reconfigurable virtual machine can allow software designers and developers to reuse parallel communication patterns. In our framework, the virtual machines can be created on-demand and their applications can be distributed at the source-code level, compiled and instantiated in runtime. (Abstract shortened by UMI.) Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .K56. Source: Masters Abstracts International, Volume: 44-03, page: 1405. Thesis (M.Sc.)--University of Windsor (Canada), 2005

A HyperNet Architecture

Network virtualization is becoming a fundamental building block of future Internet architectures. By adding networking resources into the “cloud”, it is possible for users to rent virtual routers from the underlying network infrastructure, connect them with virtual channels to form a virtual network, and tailor the virtual network (e.g., load application-specific networking protocols, libraries and software stacks on to the virtual routers) to carry out a specific task. In addition, network virtualization technology allows such special-purpose virtual networks to co-exist on the same set of network infrastructure without interfering with each other. Although the underlying network resources needed to support virtualized networks are rapidly becoming available, constructing a virtual network from the ground up and using the network is a challenging and labor-intensive task, one best left to experts. To tackle this problem, we introduce the concept of a HyperNet, a pre-built, pre-configured network package that a user can easily deploy or access a virtual network to carry out a specific task (e.g., multicast video conferencing). HyperNets package together the network topology configuration, software, and network services needed to create and deploy a custom virtual network. Users download HyperNets from HyperNet repositories and then “run” them on virtualized network infrastructure much like users download and run virtual appliances on a virtual machine. To support the HyperNet abstraction, we created a Network Hypervisor service that provides a set of APIs that can be called to create a virtual network with certain characteristics. To evaluate the HyperNet architecture, we implemented several example Hyper-Nets and ran them on our prototype implementation of the Network Hypervisor. Our experiments show that the Hypervisor API can be used to compose almost any special-purpose network – networks capable of carrying out functions that the current Internet does not provide. Moreover, the design of our HyperNet architecture is highly extensible, enabling developers to write high-level libraries (using the Network Hypervisor APIs) to achieve complicated tasks

Network architecture for large-scale distributed virtual environments

Distributed Virtual Environments (DVEs) provide 3D graphical computer generated environments with stereo sound, supporting real-time collaboration between potentially large numbers of users distributed around the world. Early DVEs has been used over local area networks (LANs). Recently with the Internet's development into the most common embedding for DVEs these distributed applications have been moved towards an exploiting IP networks. This has brought the scalability challenges into the DVEs evolution. The network bandwidth resource is the more limited resource of the DVE system and to improve the DVE's scalability it is necessary to manage carefully this resource. To achieve the saving in the network bandwidth the different types of the network traffic that is produced by the DVEs have to be considered. DVE applications demand· exchange of the data that forms different types of traffic such as a computer data type, video and audio, and a 3D data type to keep the consistency of the application's state. The problem is that the meeting of the QoS requirements of both control and continuous media traffic already have been covered by the existing research. But QoS for transfer of the 3D information has not really been considered. The 3D DVE geometry traffic is very bursty in nature and places a high demands on the network for short intervals of time due to the quite large size of the 3D models and the DVE application requirements to transmit a 3D data as quick as possible. The main motivation in carrying out the work presented in this thesis is to find a solution to improve the scalability of the DVE applications by a consideration the QoS requirements of the 3D DVE geometrical data type. In this work we are investigating the possibility to decrease the network bandwidth utilization by the 3D DVE traffic using the level of detail (LOD) concept and the active networking approach. The background work of the thesis surveys the DVE applications and the scalability requirements of the DVE systems. It also discusses the active networks and multiresolution representation and progressive transmission of the 3D data. The new active networking approach to the transmission of the 3D geometry data within the DVE systems is proposed in this thesis. This approach enhances the currently applied peer-to-peer DVE architecture by adding to the peer-to-peer multicast neny_ork layer filtering of the 3D flows an application level filtering on the active intermediate nodes. The active router keeps the application level information about the placements of users. This information is used by active routers to prune more detailed 3D data flows (higher LODs) in the multicast tree arches that are linked to the distance DVE participants. The exploration of possible benefits of exploiting the proposed active approach through the comparison with the non-active approach is carried out using the simulation­based performance modelling approach. Complex interactions between participants in DVE application and a large number of analyzed variables indicate that flexible simulation is more appropriate than mathematical modelling. To build a test bed will not be feasible. Results from the evaluation demonstrate that the proposed active approach shows potential benefits to the improvement of the DVE's scalability but the degree of improvement depends on the users' movement pattern. Therefore, other active networking methods to support the 3D DVE geometry transmission may also be required

Computer Science Research Institute 2004 annual report of activities.

This report summarizes the activities of the Computer Science Research Institute (CSRI) at Sandia National Laboratories during the period January 1, 2004 to December 31, 2004. During this period the CSRI hosted 166 visitors representing 81 universities, companies and laboratories. Of these 65 were summer students or faculty. The CSRI partially sponsored 2 workshops and also organized and was the primary host for 4 workshops. These 4 CSRI sponsored workshops had 140 participants--74 from universities, companies and laboratories, and 66 from Sandia. Finally, the CSRI sponsored 14 long-term collaborative research projects and 5 Sabbaticals

Leveraging Relational Structure through Message Passing for Modelling Non-Euclidean Data

Modelling non-Euclidean data is difficult since objects for comparison can be formed of different numbers of constituent parts with different numbers of relations between them, and traditional (Euclidean) methods are non-trivial to apply. Message passing enables such modelling by leveraging the structure of the relations within a (or between) given object(s) in order to represent and compare structure in a vectorized form of fixed dimensions. In this work, we contribute novel message passing techniques that improve state of the art for non-Euclidean modelling in a set of specifically chosen domains. In particular, (1) we introduce an attention-based structure-aware global pooling operator for graph classification and demonstrate its effectiveness on a range of chemical property prediction benchmarks, we also show that our method outperforms state of the art graph classifiers in a graph isomorphism test, and demonstrate the interpretability of our method with respect to the learned attention coefficients. (2) We propose a style similarity measure for Boundary Representations (B-Reps) that leverages the style signals in the second order statistics of the activations in a pre-trained (unsupervised) 3D encoder, and learns their relative importance to an end-user through few-shot learning. Our approach differs from existing data-driven 3D style methods since it may be used in completely unsupervised settings. We show quantitatively that our proposed method with B-Reps is able to capture stronger style signals than alternative methods on meshes and point clouds despite its significantly greater computational efficiency. We also show it is able to generate meaningful style gradients with respect to the input shape. (3) We introduce a novel message passing-based model of computation and demonstrate its effectiveness in expressing the complex dependencies of biological systems necessary to model life-like systems and tracing cell lineage during cancerous tumour growth, and demonstrate the improvement over existing methods in terms of post-analysis