DECK: A new model for a distributed executive kernel integrating communication and multithreading for support of distributed object oriented application with fault tolerance support

DECK (Distributed Executive Communication Kernel) is a communication layer that provides support for multithreading and fault tolerance support. The approach retained in DECK is close to other distributed communication kernels like PM2, Athapascan, Nexus, TPVM or Chant in its way to integrate communication and multithreading to efficiently overlap communication by computation and provide low latency remote thread creation mechanisms. However, DECK differs from these communication kernels from the services offered and its modular architecture. The main goal of DECK is to implement a new model for the design of distributed executive kernel to efficiently use the new underlying hardware architectures (SMP architectures and fast communication adapters like Myrinet or memory oriented adapter like SCI) and provide a portable layer that abstract the problems linked with the integration of communication and multithreading while offering support for heterogeneity. A great lack in the current implementation of communication libraries or distributed executive kernel is the support for basic services at the thread level and support for fault tolerance support. Indeed, communication library like PVM or MPI are often used as communication layer to ensure portability and take benefits of specific implementation to ensure a good efficiency on specific architectures however the support for fault tolerance support, multithreading, scalability and interoperability are usually not offered. In the case of DECK, we propose a model where a distributed application can dynamically instantiate clusters of processes among an heterogeneous network of computers or parallel machines and this using multiple communication protocols or communication interfaces to ensure good performances regarding the underlying hardware architecture. The programming model proposed offer both classic synchronous and asynchronous remote service calls for thread creation and message passing for synchronization and data exchange. These basic functionalities, that form the low level communication and execution layer of DECK, are enforced by a service layer that propose the basic fault tolerant services like naming and group services or data management services for the marshaling and un-marshalling of complex data structures. The layered and modular approach followed by DECK enable many other extensions while keeping a high degree of portability and efficiency.Sistemas Distribuidos - Redes ConcurrenciaRed de Universidades con Carreras en Informática (RedUNCI

Computing in the RAIN: a reliable array of independent nodes

The RAIN project is a research collaboration between Caltech and NASA-JPL on distributed computing and data-storage systems for future spaceborne missions. The goal of the project is to identify and develop key building blocks for reliable distributed systems built with inexpensive off-the-shelf components. The RAIN platform consists of a heterogeneous cluster of computing and/or storage nodes connected via multiple interfaces to networks configured in fault-tolerant topologies. The RAIN software components run in conjunction with operating system services and standard network protocols. Through software-implemented fault tolerance, the system tolerates multiple node, link, and switch failures, with no single point of failure. The RAIN-technology has been transferred to Rainfinity, a start-up company focusing on creating clustered solutions for improving the performance and availability of Internet data centers. In this paper, we describe the following contributions: 1) fault-tolerant interconnect topologies and communication protocols providing consistent error reporting of link failures, 2) fault management techniques based on group membership, and 3) data storage schemes based on computationally efficient error-control codes. We present several proof-of-concept applications: a highly-available video server, a highly-available Web server, and a distributed checkpointing system. Also, we describe a commercial product, Rainwall, built with the RAIN technology

Performance evaluation of Fast Ethernet, ATM and Myrinet under PVM

Congestion in network switches can limit the communication traffic between Parallel Virtual Machine (PVM) nodes in a parallel computation. The research introduces a new benchmark to evaluate the performance of PVM in various networking environments. The benchmark is used to achieve a better understanding of performance limitations in parallel computing that are imposed by the choice of the network. The networks considered here are Fast Ethernet, Asynchronous Transfer Mode (ATM) OC-3c (155Mb/s) and Myrinet. Together, they represent an interesting range of alternatives for parallel cluster computing. A characterization of network delays and throughput and a comparison of the expected costs of the three environments are developed to provide a basis for an informed decision on the networking methods and topology for a parallel database that is being considered for FBI\u27s National DNA Indexing System (NDIS)[17]. This network is used for communications among the nodes of the parallel machine; thus the security requirements defined for the FBI\u27s Criminal Justice Information Services Division Wide Area Network (CJIS-WAN) [12] are not a concern

A proactive fault tolerance framework for high performance computing (HPC) systems in the cloud

High Performance Computing (HPC) systems have been widely used by scientists and researchers in both industry and university laboratories to solve advanced computation problems. Most advanced computation problems are either data-intensive or computation-intensive. They may take hours, days or even weeks to complete execution. For example, some of the traditional HPC systems computations run on 100,000 processors for weeks. Consequently traditional HPC systems often require huge capital investments. As a result, scientists and researchers sometimes have to wait in long queues to access shared, expensive HPC systems. Cloud computing, on the other hand, offers new computing paradigms, capacity, and flexible solutions for both business and HPC applications. Some of the computation-intensive applications that are usually executed in traditional HPC systems can now be executed in the cloud. Cloud computing price model eliminates huge capital investments. However, even for cloud-based HPC systems, fault tolerance is still an issue of growing concern. The large number of virtual machines and electronic components, as well as software complexity and overall system reliability, availability and serviceability (RAS), are factors with which HPC systems in the cloud must contend. The reactive fault tolerance approach of checkpoint/restart, which is commonly used in HPC systems, does not scale well in the cloud due to resource sharing and distributed systems networks. Hence, the need for reliable fault tolerant HPC systems is even greater in a cloud environment. In this thesis we present a proactive fault tolerance approach to HPC systems in the cloud to reduce the wall-clock execution time, as well as dollar cost, in the presence of hardware failure. We have developed a generic fault tolerance algorithm for HPC systems in the cloud. We have further developed a cost model for executing computation-intensive applications on HPC systems in the cloud. Our experimental results obtained from a real cloud execution environment show that the wall-clock execution time and cost of running computation-intensive applications in the cloud can be considerably reduced compared to checkpoint and redundancy techniques used in traditional HPC systems

Comparison and tuning of MPI implementations in a grid context

Today, clusters are often interconnected by long distance networks within grids to offer a huge number of available ressources to a range of users. MPI, the standard communication library used to write parallel applications, has been implemented for clusters. Two main features of grids: long distance networks and technological heterogeneity, raise the question of MPI efficiency in grids. This report presents an evaluation of four recent MPI implementations (MPICH2, MPICH-Madeleine, OpenMPI and GridMPI) in the french research grid: Grid'5000. The comparison is based on the execution of pingpong, NAS Parallel Benchmarks and a real application in geophysics. We show that this implementations present performance differences. Executing MPI applications on the grid can be beneficial if the parameters are well tuned. The paper details the tuning required on each implementation to get the best performances

A Survey of Fault-Tolerance and Fault-Recovery Techniques in Parallel Systems

Supercomputing systems today often come in the form of large numbers of commodity systems linked together into a computing cluster. These systems, like any distributed system, can have large numbers of independent hardware components cooperating or collaborating on a computation. Unfortunately, any of this vast number of components can fail at any time, resulting in potentially erroneous output. In order to improve the robustness of supercomputing applications in the presence of failures, many techniques have been developed to provide resilience to these kinds of system faults. This survey provides an overview of these various fault-tolerance techniques.Comment: 11 page