103 research outputs found
Performance analysis of HPC applications in the cloud
[Abstract] The scalability of High Performance Computing (HPC) applications depends heavily on the efficient support of network communications in virtualized environments. However, Infrastructure as a Service (IaaS) providers are more focused on deploying systems with higher computational power interconnected via high-speed networks rather than improving the scalability of the communication middleware. This paper analyzes the main performance bottlenecks in HPC application scalability on the Amazon EC2 Cluster Compute platform: (1) evaluating the communication performance on shared memory and a virtualized 10 Gigabit Ethernet network; (2) assessing the scalability of representative HPC codes, the NAS Parallel Benchmarks, using an important number of cores, up to 512; (3) analyzing the new cluster instances (CC2), both in terms of single instance performance, scalability and cost-efficiency of its use; (4) suggesting techniques for reducing the impact of the virtualization overhead in the scalability of communication-intensive HPC codes, such as the direct access of the Virtual Machine to the network and reducing the number of processes per instance; and (5) proposing the combination of message-passing with multithreading as the most scalable and cost-effective option for running HPC applications on the Amazon EC2 Cluster Compute platform.Ministerio de Ciencia e Innovación; TIN2010-16735Ministerio de Economía y Competitividad; AP2010-4348
Recommended from our members
A Measurement Study of ARM Virtualization Performance
ARM servers are becoming increasingly common, making server technologies such as virtualization for ARM of growing importance. We present the first in-depth study of ARM virtualization performance on ARM server hardware, including measurements of two popular ARM and x86 hypervisors, KVM and Xen. We show how the ARM hardware support for virtualization can support much faster transitions between the VM and the hypervisor, a key hypervisor operation. However, current hypervisor designs, including both KVM (Type 1) and Xen (Type 2), are not able to lever- age this performance benefit in practice for real application workloads. We discuss the reasons why and show that other factors related to hypervisor software design and implementation have a larger role in overall performance than the speed of micro architectural operations. Based on our measurements, we discuss changes to ARM's hardware virtualization support that can potentially bridge the gap to bring its faster virtual machine exit mechanism to modern Type 2 hypervisors running real applications. These changes have been incorporated into the latest ARM architecture
Scalability and performance of a virtualized SAP system
Enterprise resource planning systems (ERP), like SAP systems, build the backbone of the business processes in today’s large enterprises. This is why a weak performance of a SAP system tremendously decreases the performance of the user and thus of the enterprise. Today many SAP hosting providers make use of virtualization techniques, but disregard the impact of such solutions. In this paper we focus on the impact of virtualization solutions on the performance of SAP systems and follow a quantitative approach to ascertain several benchmark results. We make four contributions: 1) On the basis of a quantitative investigation we give a recommendation how to configure a SAP system for heavy workload. The recommendation helps to avoid hardware resource shortage. 2) We show that the average performance of a SAP system increases up to +2% if a container-based virtualization solution is used. 3) We show that the performance of a SAP system is decreased up to -33% if a Xen-based virtualization solution is used. 4) On the basis of the quantitative results we give recommendations for a new sizing process in order to meet the requirements for virtualized SAP systems
Defeating network jitter for virtual machines
Virtualization based cloud computing hosts networked applications in virtual machines (VMs), and provides each VM the desired degree of performance isolation using resource isolation mechanisms. Existing isolation solutions address heavily on resource proportionality such as CPU, memory and I/O bandwidth, but seldom focus on resource provisioning rate. Even the VM is allocated with adequate resources, if they can not be provided in a timely manner, problems such as network jitter will be very serious and significantly affect the performance of cloud applications like internet audio/video streaming. This paper systematically analyzes and illustrates the causes of unpredictable network latency in virtualized execution environments. We decouple the design goals of resource proportionality from resource provisioning rate, and adopt divide-and-conquer strategy to defeat network jitter for VMs: (1) in VMM CPU scheduling, we differentiate self-initiated I/O from event-triggered I/O, and individually map them to periodic and aperiodic real-time domains to schedule them together; (2) in network traffic shaping of VMs, we introduce the concept of smooth window to smooth network latency and apply closed-loop feedback control to maintain network resource consumption. We implement our solutions in Xen 4.1.0 and Linux 2.6.32.13. The experimental results with both real-life applications and low-level benchmarks show that our solutions can significantly reduce network jitter, and meanwhile effectively maintain resource proportionality.published_or_final_versionThe 4th IEEE International Conference on Utility and Cloud Computing (UCC 2011), Victoria, NSW, 5-8 December 2011. In Proceedings of the 4th IEEE-UCC, 2011, p. 65-7
Supporting soft real-time tasks in the xen hypervisor
Virtualization technology enables server consolidation and has given an impetus to low-cost green data centers. However, current hypervisors do not provide adequate support for real-time applications, and this has limited the adoption of virtualization in some domains. Soft real-time applications, such as media-based ones, are impeded by components of virtualization including low-performance virtualization I/O, increased scheduling latency, and shared-cache contention. The virtual machine scheduler is central to all these issues. The goal in this paper is to adapt the virtual machine scheduler to be more soft-real-time friendly. We improve two aspects of the VMM scheduler – managing scheduling latency as a first-class resource and managing shared caches. We use enterprise IP telephony as an illustrative soft real-time workload and design a scheduler S that incorporates th
A SOFTWARE DEFINED NETWORKING ARCHITECTURE FOR HIGH PERFORMANCE CLOUDS 1
ABSTRACT-Multi-tenant clouds with resource virtualization offer elasticity of resources and elimination of initial cluster setup cost and time for applications. However, poor network performance, performance variation and noisy neighbors are some of the challenges for execution of high performance applications on public clouds. Utilizing these virtualized resources for scientific applications, which have complex communication patterns, require low latency communication mechanisms and a rich set of communication constructs. To minimize the virtualization overhead, a novel approach for low latency networking for HPC Clouds is proposed and implemented over a multi-technology software defined network. The efficiency of the proposed low-latency SDN is analyzed and evaluated for high performance applications. The results of the experiments show that the latest Mellanox FDR InfiniBand interconnect and Mellanox OpenStack plugin gives the best performance for implementing virtual machine based high performance clouds with large message sizes
- …