dReDBox: Materializing a full-stack rack-scale system prototype of a next-generation disaggregated datacenter

Current datacenters are based on server machines, whose mainboard and hardware components form the baseline, monolithic building block that the rest of the system software, middleware and application stack are built upon. This leads to the following limitations: (a) resource proportionality of a multi-tray system is bounded by the basic building block (mainboard), (b) resource allocation to processes or virtual machines (VMs) is bounded by the available resources within the boundary of the mainboard, leading to spare resource fragmentation and inefficiencies, and (c) upgrades must be applied to each and every server even when only a specific component needs to be upgraded. The dRedBox project (Disaggregated Recursive Datacentre-in-a-Box) addresses the above limitations, and proposes the next generation, low-power, across form-factor datacenters, departing from the paradigm of the mainboard-as-a-unit and enabling the creation of function-block-as-a-unit. Hardware-level disaggregation and software-defined wiring of resources is supported by a full-fledged Type-1 hypervisor that can execute commodity virtual machines, which communicate over a low-latency and high-throughput software-defined optical network. To evaluate its novel approach, dRedBox will demonstrate application execution in the domains of network functions virtualization, infrastructure analytics, and real-time video surveillance.This work has been supported in part by EU H2020 ICTproject dRedBox, contract #687632.Peer ReviewedPostprint (author's final draft

Glider: A GPU Library Driver for Improved System Security

Legacy device drivers implement both device resource management and isolation. This results in a large code base with a wide high-level interface making the driver vulnerable to security attacks. This is particularly problematic for increasingly popular accelerators like GPUs that have large, complex drivers. We solve this problem with library drivers, a new driver architecture. A library driver implements resource management as an untrusted library in the application process address space, and implements isolation as a kernel module that is smaller and has a narrower lower-level interface (i.e., closer to hardware) than a legacy driver. We articulate a set of device and platform hardware properties that are required to retrofit a legacy driver into a library driver. To demonstrate the feasibility and superiority of library drivers, we present Glider, a library driver implementation for two GPUs of popular brands, Radeon and Intel. Glider reduces the TCB size and attack surface by about 35% and 84% respectively for a Radeon HD 6450 GPU and by about 38% and 90% respectively for an Intel Ivy Bridge GPU. Moreover, it incurs no performance cost. Indeed, Glider outperforms a legacy driver for applications requiring intensive interactions with the device driver, such as applications using the OpenGL immediate mode API

Interactive Real-Time Embedded Systems Education Infused with Applied Internet Telephony

The transition from traditional circuit-switched phone systems to modern packet-based Internet telephony networks demands tools to support Voice over Internet Protocol (VoIP) development. In this paper, we introduce the XinuPhone, an integrated hardware/software approach for educating users about VoIP technology on a real-time embedded platform. We propose modular course topics for design-oriented, hands-on laboratory exercises: filter design, timing, serial communications, interrupts and resource budgeting, network transmission, and system benchmarking. Our open-source software platform encourages development and testing of new CODECs alongside existing standards, unlike similar commercial solutions. Furthermore, the supporting hardware features inexpensive, readily available components designed specifically for educational and research users on a limited budget. The XinuPhone is especially good for experimenting with design trade-offs as well as interactions between real-time software and hardware components

An Energy-Efficient IoT node for HMI applications based on an ultra-low power Multicore Processor

Developing wearable sensing technologies and unobtrusive devices is paving the way to the design of compelling applications for the next generation of systems for a smart IoT node for Human Machine Interaction (HMI). In this paper we present a smart sensor node for IoT and HMI based on a programmable Parallel Ultra-Low-Power (PULP) platform. We tested the system on a hand gesture recognition application, which is a preferred way of interaction in HMI design. A wearable armband with 8 EMG sensors is controlled by our IoT node, running a machine learning algorithm in real-time, recognizing up to 11 gestures with a power envelope of 11.84 mW. As a result, the proposed approach is capable to 35 hours of continuous operation and 1000 hours in standby. The resulting platform minimizes effectively the power required to run the software application and thus, it allows more power budget for high-quality AFE

High-speed dynamic partial reconfiguration for field programmable gate arrays

With dynamically and partially reconfigurable designs, it is necessary that the speed of the reconfiguration be accomplished in a time that is sufficiently small such that the operation of reconfiguration is not the limiting factor in the process. Therefore, the communication between the source of configuration and the configurable unit must be made as fast as possible. The aim of this work is to use an embedded controller internal to the FPGA to control the reconfiguration process and obtain the maximum speed at which reconfiguration can occur, with current FPGA technology. The use of Direct Memory Access (DMA) driven operations instead of the current arbitrated bus architectures yielded a 30% increase in the speed of reconfiguration compared to other methods such as OPB_HWICAP and PLB_HWICAP [1]. The use of interrupt driven partial reconfiguration was also introduced, allowing the processor to switch to other tasks during the reconfiguration operation. All of these contributions lead to significant performance improvements over current partial reconfiguration subsystems. The configuration controller was tested using four partially reconfigurable system implementations: (i) one targeting the Hard IP PowerPC405 on Virtex-4, (ii) a second targeting the Soft IP MicroBlaze on Virtex-5, (iii) a third targeting the Hard IP PowerPC440 on Virtex-5, and (iv) a fourth system targets the Hard IP PowerPC440 on Virtex-5 capable of adaptive feedback. The adaptive feedback Virtex-5 system can use internal voltage and temperature measurements from the Xilinx System Monitor IP to dynamically increase or decrease the speed of reconfiguration and/or change other reconfigurable aspects of the system to better match the environment