Institut für Informatik und Computational Science
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In this paper we report about the recently completed porting of GAMMA to the Netgear GA621 Gigabit Ethernet adapter, and provide a comparison among GAMMA, MPI/GAMMA, TCP/IP, and MPICH/TCP, based on the Netgear GA621 and the older Netgear GA620 network adapters and using different device drivers, in a Gigabit Ethernet cluster of PCs running Linux 2.4. GAMMA (the Genoa Active Message MAchine) is a lightweight messaging system based on an Active Message-like paradigm, originally designed for efficient exploitation of Fast Ethernet interconnects. The comparison includes simple latency/hspace{0pt}bandwidth evaluation of the messaging systems on both adapters, as well as performance comparisons based on the NAS NPB and an end-user fluid dynamics application called Modular Ocean Model (MOM). The analysis of results provides useful hints concerning the efficient use of Gigabit Ethernet with clusters of PCs. In particular, it emerges that GAMMA on the GA621 adapter, with a combination of low end-to-end latency (8.5 $mu$s) and high throughput (118.4 MByte/s), provides a performing, cost-effective alternative to proprietary high-speed networks, e.g.~Myrinet, for a wide range of cluster computing applications.
Characterizing Grids
(2003)
We present a new data model approach to describe the various objects that either represent the Grid infrastructure or make use of it. The data model is based on the experiences and experiments conducted in heterogeneous Grid environments. While very sophisticated data models exist to describe and characterize e.g. compute capacities or web services, we will show that a general description, which combines {em all} of these aspects, is needed to give an adequate representation of objects on a Grid. The Grid Object Description Language (GODsL)} is a generic and extensible approach to unify the various aspects that an object on a Grid can have. GODsL provides the content for the XML based communication in Grid migration scenarios, carried out in the GridLab project. We describe the data model architecture on a general level and focus on the Grid application scenarios.
In order to take full advantage of Grid environments, applications need to be able to run on various heterogeneous platforms. Distributed runs across several clusters or supercomputers for example, require matching binaries at each site. Thus, at some stage, each Grid enabled application needs to be recompiled for every platform. Up to now, creating matching binaries on different platforms was a manual, sequential, slow, and very error-prone process. Developers had to log into each machine, transfer source code, check consistency and recompile if necessary. This cumbersome procedure is surely one reason for the (still existing) lack of production Grid computing. Gridmake, a tool to automate and speed up this procedure is presented in this paper.
This paper analyses data privacy issues as they arise from different deployment scenarios for networks that use embedded sensor devices. Maintaining data privacy in pervasive environments requires the management and implementation of privacy protection measures close to the data source. We propose a set of atomic privacy parameters that is generic enough to form specific privacy classes and might be applied directly at the embedded sensor device.
Today, InfiniBand is an evolving high speed interconnect technology to build high performance computing clusters, that achieve top 10 rankings in the current top 500 of the worldwide fastest supercomputers. Network interfaces (called host channel adapters) provide transport layer services over connections and datagrams in reliable or unreliable manner. Additionally, InfiniBand supports remote direct memory access (RDMA) primitives that allow for one- sided communication. Using server load balancing together with a high performance cluster makes it possible to build a fast, scalable, and reliable service infrastructure. We have designed and implemented a scalable load balancer for InfiniBand clusters called SLIBNet. Our investigations show that the InfiniBand architecture offers features which perfectly support load balancing. We want to thank the Megware Computer GmbH for providing us an InfiniBand switch to realize a server load balancing testbed.
With the next generation Internet protocol IPv6 at the horizon, it is time to think about how applications can migrate to IPv6. Web traffic is currently one of the most important applications in the Internet. The increasing popularity of dynamically generated content on the World Wide Web, has created the need for fast web servers. Server clustering together with server load balancing has emerged as a promising technique to build scalable web servers. The paper gives a short overview over the new features of IPv6 and different server load balancing technologies. Further, we present and evaluate Loaded, an user-space server load balancer for IPv4 and IPv6 based on Linux.
Design Issues in the Implementation of MPI2 One Sided Communication in Ethernet based Networks
(2007)
In current research, one sided communication of the MPI2 standard is pushed as a promising technique [6, 7, 10, 18]. But measurements of applications and MPI2 primitives show a different picture [17]. In this paper we analyze de sign issues of MPI2 one sided communication and its im plementations. We focus on asynchronous communication for parallel applications in Ethernet cluster environments. Further, one sided communication is compared to two sided communication. This paper will prove that the key problem to performance is not only the implementation of MPI2 one sided communication - it is the design.
In this paper we present the design and implementation of the Migol brokering framework. Migol is a Grid middleware, which addresses the fault-tolerance of long-running and compute-intensive applications. The framework supports e. g. the automatic and transparent recovery respectively the migration of applications. Another core feature of Migol is the discovery, selection, and allocation of resources using advance reservation. Grid broker systems can significantly benefit from advance reservation. With advance reservation brokers and users can obtain execution guarantees from local resource management systems (LRM) without requiring detailed knowledge of current and future workloads or of the resource owner's policies. Migol's Advance Reservation Service (ARS) provides an adapter layer for reservation capabilities of different LRMs, which is currently not provided by existing Grid middleware platforms. Further, we propose a shortest expected delay (SED) strategy for scheduling of advance reservations within the Job Broker Service. SED needs information about the earliest start time of an application. This is currently not supported by LRMs. We added this feature for PBSPro. Migol depends on Globus and its security infrastructure. Our performance experiments show the substantial overhead of this serviceoriented approach.
Especially for sciences the provision of massive parallel CPU capacity is one of the most attractive features of a grid. A major challenge in a distributed, inherently dynamic grid is fault tolerance. The more resources and components involved, the more complicated and error-prone becomes the system. In a grid with potentially thousands of machines connected to each other the reliability of individual resources cannot be guaranteed.The benefit of the grid is that in case of a failure ail application may be migrated and restarted from a checkpoint file on another site. This approach requires a service infrastructure which handles the necessary activities transparently. In this article, we present Migol, a fault-tolerant and self-healing grid middleware for MPI applications. Migol is based on open standards and extends the services of the Globus toolkit to support the fault tolerance of grid applications.Further, the Migol framework itself is designed with special focus on fault tolerance. For example, Migol eplicates ritical services and uses a ring-based replication protocol to achieve data consistency. (c) 2007 Elsevier B.V. All rights reserved.
Owing to the loose coupling between replicas, the replica-exchange (RE) class of algorithms should be able to benefit greatly from using as many resources as available. However, the ability to effectively use multiple distributed resources to reduce the time to completion remains a challenge at many levels. Additionally, an implementation of a pleasingly distributed algorithm such as replica-exchange, which is independent of infrastructural details, does not exist. This paper proposes an extensible and scalable framework based on Simple API for Grid Applications that provides a general-purpose, opportunistic mechanism to effectively use multiple resources in an infrastructure-independent way. By analysing the requirements of the RE algorithm and the challenges of implementing it on real production systems, we propose a new abstraction (BIGJOB), which forms the basis of the adaptive redistribution and effective scheduling of replicas.
This paper presents an evaluation of ACPI energy saving modes, and deduces the design and implementation of an energy saving daemon for clusters called cherub. The design of the cherub daemon is modular and extensible. Since the only requirement is a central approach for resource management, cherub is suited for Server Load Balancing (SLB) clusters managed by dispatchers like Linux Virtual Server (LVS), as well as for High Performance Computing (HPC) clusters. Our experimental results show that cherub's scheduling algorithm works well, i.e. it will save energy, if possible, and avoids state-flapping.
Scheduling performance in computational grid can potentially benefit a lot from accurate execution time estimation for parallel jobs. Most existing approaches for the parallel job execution time estimation, however, require ample past job traces and the explicit correlations between the job execution time and the outer layout parameters such as the consumed processor numbers, the user-estimated execution time and the job ID, which are hard to obtain or reveal. This paper presents and evaluates a novel execution time estimation approach for parallel jobs, the user-behavior clustering for execution time estimation, which can give more accurate execution time estimation for parallel jobs through exploring the job similarity and revealing the user submission patterns. Experiment results show that compared to the state-of-art algorithms, our approach can improve the accuracy of the job execution time estimation up to 5.6 %, meanwhile the time that our approach spends on calculation can be reduced up to 3.8 %.