1,969 research outputs found
RELEASE: A High-level Paradigm for Reliable Large-scale Server Software
Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the first six months. The project aim is to scale the Erlang’s radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the effectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene
RELEASE: A High-level Paradigm for Reliable Large-scale Server Software
Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the rst six months. The project aim is to scale the Erlang's radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the e ectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene
ATAMM analysis tool
Diagnostics software for analyzing Algorithm to Architecture Mapping Model (ATAMM) based concurrent processing systems is presented. ATAMM is capable of modeling the execution of large grain algorithms on distributed data flow architectures. The tool graphically displays algorithm activities and processor activities for evaluation of the behavior and performance of an ATAMM based system. The tool's measurement capabilities indicate computing speed, throughput, concurrency, resource utilization, and overhead. Evaluations are performed on a simulated system using the software tool. The tool is used to estimate theoretical lower bound performance. Analysis results are shown to be comparable to the predictions
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
Byzantine Fault Tolerance for Distributed Systems
The growing reliance on online services imposes a high dependability requirement on the computer systems that provide these services. Byzantine fault tolerance (BFT) is a promising technology to solidify such systems for the much needed high dependability. BFT employs redundant copies of the servers and ensures that a replicated system continues providing correct services despite the attacks on a small portion of the system. In this dissertation research, I developed novel algorithms and mechanisms to control various types of application nondeterminism and to ensure the long-term reliability of BFT systems via a migration-based proactive recovery scheme. I also investigated a new approach to significantly improve the overall system throughput by enabling concurrent processing using Software Transactional Memory (STM). Controlling application nondeterminism is essential to achieve strong replica consistency because the BFT technology is based on state-machine replication, which requires deterministic operation of each replica. Proactive recovery is necessary to ensure that the fundamental assumption of using the BFT technology is not violated over long term, i.e., less than one-third of replicas remain correct. Without proactive recovery, more and more replicas will be compromised under continuously attacks, which would render BFT ineffective. STM based concurrent processing maximized the system throughput by utilizing the power of multi-core CPUs while preserving strong replication consistenc
Byzantine Fault Tolerance for Distributed Systems
The growing reliance on online services imposes a high dependability requirement on the computer systems that provide these services. Byzantine fault tolerance (BFT) is a promising technology to solidify such systems for the much needed high dependability. BFT employs redundant copies of the servers and ensures that a replicated system continues providing correct services despite the attacks on a small portion of the system. In this dissertation research, I developed novel algorithms and mechanisms to control various types of application nondeterminism and to ensure the long-term reliability of BFT systems via a migration-based proactive recovery scheme. I also investigated a new approach to significantly improve the overall system throughput by enabling concurrent processing using Software Transactional Memory (STM). Controlling application nondeterminism is essential to achieve strong replica consistency because the BFT technology is based on state-machine replication, which requires deterministic operation of each replica. Proactive recovery is necessary to ensure that the fundamental assumption of using the BFT technology is not violated over long term, i.e., less than one-third of replicas remain correct. Without proactive recovery, more and more replicas will be compromised under continuously attacks, which would render BFT ineffective. STM based concurrent processing maximized the system throughput by utilizing the power of multi-core CPUs while preserving strong replication consistenc
System Description for a Scalable, Fault-Tolerant, Distributed Garbage Collector
We describe an efficient and fault-tolerant algorithm for distributed cyclic
garbage collection. The algorithm imposes few requirements on the local
machines and allows for flexibility in the choice of local collector and
distributed acyclic garbage collector to use with it. We have emphasized
reducing the number and size of network messages without sacrificing the
promptness of collection throughout the algorithm. Our proposed collector is a
variant of back tracing to avoid extensive synchronization between machines. We
have added an explicit forward tracing stage to the standard back tracing stage
and designed a tuned heuristic to reduce the total amount of work done by the
collector. Of particular note is the development of fault-tolerant cooperation
between traces and a heuristic that aggressively reduces the set of suspect
objects.Comment: 47 pages, LaTe
Exploiting replication in distributed systems
Techniques are examined for replicating data and execution in directly distributed systems: systems in which multiple processes interact directly with one another while continuously respecting constraints on their joint behavior. Directly distributed systems are often required to solve difficult problems, ranging from management of replicated data to dynamic reconfiguration in response to failures. It is shown that these problems reduce to more primitive, order-based consistency problems, which can be solved using primitives such as the reliable broadcast protocols. Moreover, given a system that implements reliable broadcast primitives, a flexible set of high-level tools can be provided for building a wide variety of directly distributed application programs
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