Abstract-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 multitray 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-ina-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.
Abstract-Power consumption and high compute density are the key factors to be considered when building a compute node for the upcoming Exascale revolution. Current architectural design and manufacturing technologies are not able to provide the requested level of density and power efficiency to realise an operational Exascale machine. A disruptive change in the hardware design and integration process is needed in order to cope with the requirements of this forthcoming computing target. This paper presents the ExaNoDe H2020 research project aiming to design a highly energy efficient and highly integrated heterogeneous compute node targeting Exascale level computing, mixing low-power processors, heterogeneous co-processors and using advanced hardware integration technologies with the novel UNIMEM Global Address Space memory system.
Remote DMA (RDMA) engines are widely used in clusters/data-centres to improve the performance of data transfers between applications running on different nodes of a computing system. RDMAs are today supported by most network architectures and distributed programming models. However, with the massive usage of virtualization most applications will use RDMAs from virtual machines, and the virtualization of such I/O devices poses several challenges. This paper describes a generic para-virtualization framework based on API Remoting, providing at the same time the flexibility of software based virtualization, and the low overhead of hardware-assisted solutions.The solution presented in this paper is targeting the KVM hypervisor, but is not bound to any target network architecture or specific RDMA engine, thanks to the virtualization at the level of the programming API. In addition, two of the major limitations of para-virtualization are addressed: data sharing between host and guest, and interactions between guests and hypervisor. A set of experimental results showed a near to native performance for the final user of the RDMA (i.e., maximum transfer bandwidth), with a higher overhead only to simulate the API functions used to initialize the RDMA device or allocate/deallocate RDMA buffers.
In the context of system emulation, the sophistication of the emulator usually grows with the complexity of the target system model. Particularly, emulating precisely a certain CPU architecture can introduce many challenges that have to be properly explored and somehow solved to reach an accurate emulation of the target system.In this paper we present an implementation design of ARM atomic instructions for a multi-threaded version of QEMU (the Quick EMUlator), currently under development [1].To prove the correctness and performance of such an implementation, some tests have been performed showcasing a high degree of accuracy and fidelity of the emulated instructions. While this paper does not cover all possible guest architectures that QEMU supports, the described new approach results in a reliable infrastructure that eventually can address all target architectures in QEMU.
Cyber-physical systems (CPS) are devices with sensors and actuators which link the physical with the virtual world. There is a strong trend towards open systems, which can be extended during operation by instantly adding functionalities on demand. We discuss this trend in the context of automotive, medical and industrial automation systems. The goal of this chapter is to elaborate the research challenges of ensuring security in these new platforms for such open systems. A main problem is that such CPS apps shall be able to access and modify safety critical device internals. Cyber-physical attacks can affect the integrity, availability and confidentiality in CPS. Examples range from deception based attacks such as false-data-injection, sensor and actuator attacks, replay attacks, and also denial-of-service attacks. Hence, new methods are required to develop an end-to-end solution for development and deployment of trusted apps. This chapter presents the architecture approach and its key components, and methods for open CPS apps, including tool chain and development support.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.