Enhancing HPC on Virtual Systems in Clouds through Optimizing Virtual Overlay Networks

Virtual Ethernet overlay provides a powerful model for realizing virtual distributed and parallel computing systems with strong isolation, portability, and recoverability properties. However, in extremely high throughput and low latency networks, such overlays can suffer from bandwidth and latency limitations, which is of particular concern in HPC environments. Through a careful and quantitative analysis, I iden- tify three core issues limiting performance: delayed and excessive virtual interrupt delivery into guests, copies between host and guest data buffers during encapsulation, and the semantic gap between virtual Ethernet features and underlying physical network features. I propose three novel optimizations in response: optimistic timer- free virtual interrupt injection, zero-copy cut-through data forwarding, and virtual TCP offload. These optimizations improve the latency and bandwidth of the overlay network on 10 Gbps Ethernet and InfiniBand interconnects, resulting in near-native performance for a wide range of microbenchmarks and MPI application benchmarks

ASETS: A SDN Empowered Task Scheduling System for HPCaaS on the Cloud

With increasing demands for High Performance Computing (HPC), new ideas and methods are emerged to utilize computing resources more efficiently. Cloud Computing appears to provide benefits such as resource pooling, broad network access and cost efficiency for the HPC applications. However, moving the HPC applications to the cloud can face several key challenges, primarily, the virtualization overhead, multi-tenancy and network latency. Software-Defined Networking (SDN) as an emerging technology appears to pave the road and provide dynamic manipulation of cloud networking such as topology, routing, and bandwidth allocation. This paper presents a new scheme called ASETS which targets dynamic configuration and monitoring of cloud networking using SDN to improve the performance of HPC applications and in particular task scheduling for HPC as a service on the cloud (HPCaaS). Further, SETSA, (SDN-Empowered Task Scheduler Algorithm) is proposed as a novel task scheduling algorithm for the offered ASETS architecture. SETSA monitors the network bandwidth to take advantage of its changes when submitting tasks to the virtual machines. Empirical analysis of the algorithm in different case scenarios show that SETSA has significant potentials to improve the performance of HPCaaS platforms by increasing the bandwidth efficiency and decreasing task turnaround time. In addition, SETSAW, (SETSA Window) is proposed as an improvement of the SETSA algorithm

Exploring Scientific Application Performance Using Large Scale Object Storage

One of the major performance and scalability bottlenecks in large scientific applications is parallel reading and writing to supercomputer I/O systems. The usage of parallel file systems and consistency requirements of POSIX, that all the traditional HPC parallel I/O interfaces adhere to, pose limitations to the scalability of scientific applications. Object storage is a widely used storage technology in cloud computing and is more frequently proposed for HPC workload to address and improve the current scalability and performance of I/O in scientific applications. While object storage is a promising technology, it is still unclear how scientific applications will use object storage and what the main performance benefits will be. This work addresses these questions, by emulating an object storage used by a traditional scientific application and evaluating potential performance benefits. We show that scientific applications can benefit from the usage of object storage on large scales.Comment: Preprint submitted to WOPSSS workshop at ISC 201

Data centre optimisation enhanced by software defined networking

Contemporary Cloud Computing infrastructures are being challenged by an increasing demand for evolved cloud services characterised by heterogeneous performance requirements including real-time, data-intensive and highly dynamic workloads. The classical way to deal with dynamicity is to scale computing and network resources horizontally. However, these techniques must be coupled effectively with advanced routing and switching in a multi-path environment, mixed with a high degree of flexibility to support dynamic adaptation and live-migration of virtual machines (VMs). We propose a management strategy to jointly optimise computing and networking resources in cloud infrastructures, where Software Defined Networking (SDN) plays a key enabling role

Software-Defined Cloud Computing: Architectural Elements and Open Challenges

The variety of existing cloud services creates a challenge for service providers to enforce reasonable Software Level Agreements (SLA) stating the Quality of Service (QoS) and penalties in case QoS is not achieved. To avoid such penalties at the same time that the infrastructure operates with minimum energy and resource wastage, constant monitoring and adaptation of the infrastructure is needed. We refer to Software-Defined Cloud Computing, or simply Software-Defined Clouds (SDC), as an approach for automating the process of optimal cloud configuration by extending virtualization concept to all resources in a data center. An SDC enables easy reconfiguration and adaptation of physical resources in a cloud infrastructure, to better accommodate the demand on QoS through a software that can describe and manage various aspects comprising the cloud environment. In this paper, we present an architecture for SDCs on data centers with emphasis on mobile cloud applications. We present an evaluation, showcasing the potential of SDC in two use cases-QoS-aware bandwidth allocation and bandwidth-aware, energy-efficient VM placement-and discuss the research challenges and opportunities in this emerging area.Comment: Keynote Paper, 3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI 2014), September 24-27, 2014, Delhi, Indi