Hadi Bannazadeh

FPGAs in the Cloud: Booting Virtualized Hardware Accelerators with OpenStack

General-purpose computing on an ever-broadening array of parallel devices has led to an increasingly complex and multi-dimensional landscape with respect to programmability and performance optimization. The growing diversity of parallel architectures presents many challenges to the domain scientist, including device selection, programming model, and level of investment in optimization. All of these choices influence the balance between programmability and performance. In this paper, we characterize the performance achievable across a range of optimizations, along with their programmability, for multi- and many-core platforms - specifically, an Intel Sandy Bridge CPU, Intel Xeon Phi co-processor, and NVIDIA Kepler K20 GPU - in the context of an n-body, molecular-modeling application called GEM. Our systematic approach to optimization delivers implementations with speed-ups of 194.98×, 885.18×, and 1020.88× on the CPU, Xeon Phi, and GPU, respectively, over the naive serial version. Beyond the speed-ups, we characterize the incremental optimization of the code from naive serial to fully hand-tuned on each platform through four distinct phases of increasing complexity to expose the strengths and weaknesses of the programming models offered by each platform.This paper focuses on an important research problem of Big Data classification in intrusion detection system. Deep Belief Networks is introduced to the field of intrusion detection, and an intrusion detection model based on Deep Belief Networks is proposed to apply in intrusion recognition domain. The deep hierarchical model is a deep neural network classifier of a combination of multilayer unsupervised learning networks, which is called as Restricted Boltzmann Machine, and a supervised learning network, which is called as Back-propagation network. The experimental results on KDD CUP 1999 dataset demonstrate that the performance of Deep Belief Networks model is better than that of SVM and ANN.

Routing Algorithms for Network Function Virtualization Enabled Multicast Topology on SDN

Many multicast services such as live multimedia distribution and real-time event monitoring require multicast mechanisms that involve network functions (e.g., firewall and video transcoding). Network function virtualization (NFV) is a concept that proposes using virtualization to implement network functions on infrastructure building block (such as high volume servers and virtual machines), where software provides the functionality of existing purpose-built network equipment. We present an approach for building the multicast mechanism whereby multicast flows are processed by NFV before reaching their end users. We propose a routing algorithm and a method for building an appropriate multicast topology.

Software-Defined Infrastructure and the SAVI Testbed

In this paper we consider Software-Defined Infrastructure (SDI), a new concept for integrated control and management of converged heterogeneous resources. SDI enables programmability of infrastructure by enabling the support of cloud-based applications, customized network functions, and hybrid combinations of these. We motivate SDI in the context of a multi-tier cloud that includes massive-scale datacenters as well as a smart converged network edge. In SDI, a centralized SDI manager controls converged heterogeneous resources (i.e., computing, programmable hardware, and networking resources) using virtualization and a topology manager that provides the status of all resources and their connectivity. We discuss the design and implementation of SDI in the context of the Canadian SAVI testbed. We describe the current deployment of the SAVI testbed and applications that are currently supported in the testbed.

Software-defined infrastructure and the Future Central Office

This paper discusses the role of virtualization and software-defined infrastructure (SDI) in the design of future application platforms, and in particular the Future Central Office (CO). A multi-tier computing cloud is presented in which resources in the Smart Edge of the network play a crucial role in the delivery of low-latency and data-intensive applications. Resources in the Smart Edge are virtualized and managed using cloud computing principles, but these resources are more diverse than in conventional data centers, including programmable hardware, GPUs, etc. We propose an architecture for future application platforms, and we describe the SAVI Testbed (TB) design for the Smart Edge. The design features a novel Software-Defined Infrastructure manager that operates on top of OpenStack and OpenFlow. We conclude with a discussion of the implications of the Smart Edge design on the Future CO.

Enabling SDN applications on Software-Defined Infrastructure

In this paper we discuss how to enable Software-Defined Networking (SDN) applications on Software-Defined Infrastructure (SDI) which is an approach for integrated control and management of converged computing and networking resources. Current separated resource management for computing or networking resources is not sufficient for addressing applications and multimedia services that require guaranteed service and quality levels. In addition, current resource management is not capable of managing heterogeneous resources that include computing and networking resources in combination with other resources such as programmable hardware, GPUs and network processors. We present an SDI that provides pluggable resource management modules for scheduling, networking control, fault management, and so on. This paper focuses on the design and implementation of a networking control module that enables SDN applications using information available from other modules. Currently, we have deployed the network control module in the practical multi-tier cloud infrastructure, SAVI Testbed. We present real measurements that show the functional evaluation results of our network control module.

Virtualized Application Networking Infrastructure

In this paper, we present a new platform for experimenting with networked systems and distributed applications called Virtualized Application Networking Infrastructure (VANI). This infrastructure is designed as a converged communications and computing infrastructure that would facilitate operation of an open applications marketplace. VANI enables introduction of new network architectures that require in-network (hardware-accelerated) content processing and storage. We describe the VANI architecture and the resources it provides. VANI has two main planes; control and management plane, and applications plane. VANI resources are virtualized and made available to the researchers and application providers through a service-oriented control and management plane. The current VANI resources are processing, storage, networking and various software-based resources. VANI also includes a new reprogrammable hardware resource that enables experimenting with hardware-based or hardware-accelerated networking algorithms and protocols. We present performance evaluations of this reprogrammable hardware resource, and the VANI virtual networking mechanism. The results show that by using the reprogrammable hardware resource, researchers can evaluate high performance and high throughput networking algorithms as easily as evaluating software-based networking algorithms.

Monitoring and measurement in software-defined infrastructure

Software-Defined Infrastructure (SDI) presents an approach for integrated management of virtualized heterogeneous resources. Monitoring and measurement is an essential component for effective control and management. This paper presents an architecture of a system, named MonArch, based on SDI that provides integrated monitoring and measurement functionalities. Unlike existing cloud and network monitoring systems, MonArch supports execution of user-generated monitoring tasks, offers monitoring as a service to tenants, administrators as well as management modules, and provides a framework for monitoring data analytics. We have implemented and deployed MonArch in the SAVI Testbed, and our experience shows the system is able to support a wide variety of monitoring tasks while achieving high performance and scalability.

Enabling Flexible Network FPGA Clusters in a Heterogeneous Cloud Data Center

We present a framework for creating network FPGA clusters in a heterogeneous cloud data center. The FPGA clusters are created using a logical kernel description describing how a group of FPGA kernels are to be connected (independent of which FPGA these kernels are on), and an FPGA mapping file. The kernels within a cluster can be replicated with simple directives within this framework. The FPGAs can communicate to any other network device in the data center, including CPUs, GPUs, and IoT devices (such as sensors). This heterogeneous cloud manages these devices with the use of OpenStack. We observe that our infrastructure is limited due to the physical infrastructure such as the 1~Gb Ethernet connection. Our framework however can be ported to other physical infrastructures. We tested our infrastructure with a database acceleration application. This application was replicated six times across three FPGAs within our cluster and we observed a throughput increase of six times as this scaled linearly. Our framework generates the OpenStack calls needed to reserve the compute devices, creates the network connections (and retrieve MAC addresses), generate the bitstreams, programs the devices, and configure the devices with the appropriate MAC addresses, creating a ready-to-use network device that can interact with any other network device in the data center.

SAVI Testbed Architecture and Federation

The flexibility of cloud computing has afforded users the ability to develop and deploy fully customizable cloud-based applications and services. Thus far, this flexibility has primarily been constrained to the likes of x86 servers and storage devices. The SAVI application platform testbed was developed to realize the hypothesis that all physical infrastructure resources can be virtualized. Key to this work is a novel control and management framework based on Software-Defined Infrastructure (SDI), a concept which provides a unified programmable interface over heterogeneous infrastructures. In this paper, we present the architecture of the Canadian SAVI national testbed based on the SDI framework. The design of an autonomous SAVI node will be described and the multi-node deployment that comprise the national testbed will be discussed. In addition, the orchestration of applications across the multi-node testbed will be described. Lastly, we will report on the progress of our recent efforts to federate the SAVI testbed with the American GENI national testbed.

Identity access management for Multi-tier cloud infrastructures

This paper presents a novel architecture to manage identity and access (IAM) in a Multi-tier cloud infrastructure, in which most services are supported by massive-scale data centres over the Internet. Multi-tier cloud infrastructure uses tier-based model from Software Engineering to provide resources in different tires. In this paper we focus on design and implementation of a centralized identity and access management system for the multi-tier cloud infrastructure. First, we discuss identity and access management requirements in such an environment and propose our solution to address these requirements. Next, we discuss approaches to improve performance of the IAM system and make it scalable to billions of users. Finally, we present experimental results based on the current deployment in the SAVI Testbed. We show that our IAM system outperforms the previously proposed IAM systems for cloud infrastructure by factor 9 in throughput when the number of users is small, it handle about 50 times more requests in peak usage. Because our architecture is a combination of Green-thread and load balanced process, it uses less systems resources, and easily scales up to address high number of requests.