OceanStore is a utility infrastructure designed to span the globe and provide continuous access to persistent information. Since this infrastructure is comprised of untrusted servers, data is protected through redundancy and cryptographic techniques. To improve performance, data is allowed to be cached anywhere, anytime. Additionally, monitoring of usage patterns allows adaptation to regional outages and denial of service attacks; monitoring also enhances performance through pro-active movement of data. A prototype implementation is currently under development. 1

Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem. On the contrary, modern data models exacerbate it: In order to manipulate large sets of complex objects as efficiently as today’s database systems manipulate simple records, query processing algorithms and software will become more complex, and a solid understanding of algorithm and architectural issues is essential for the designer of database management software. This survey provides a foundation for the design and implementation of query execution facilities in new database management systems. It describes a wide array of practical query evaluation techniques for both relational and post-relational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.

Transactional memory (TM) simplifies parallel programming by guaranteeing that transactions appear to execute atomically and in isolation. Implementing these properties includes providing data version management for the simultaneous storage of both new (visible if the transaction commits) and old (retained if the transaction aborts) values. Most (hardware) TM systems leave old values “in place” (the target memory address) and buffer new values elsewhere until commit. This makes aborts fast, but penalizes (the much more frequent) commits. In this paper, we present a new implementation of transactional memory, Log-based Transactional Memory (LogTM), that makes commits fast by storing old values to a per-thread log in cacheable virtual memory and storing new values in place. LogTM makes two additional contributions. First, LogTM extends a MOESI directory protocol to enable both fast conflict detection on evicted blocks and fast commit (using lazy cleanup). Second, LogTM handles aborts in (library) software with little performance penalty. Evaluations running micro- and SPLASH-2 benchmarks on a 32way multiprocessor support our decision to optimize for commit by showing that only 1-2 % of transactions abort. 1.

Serialization of threads due to critical sections is a fundamental bottleneck to achieving high performance in multithreaded programs. Dynamically, such serialization may be unnecessary because these critical sections could have safely executed concurrently without locks. Current processors cannot fully exploit such parallelism because they do not have mechanisms to dynamically detect such false inter-thread dependences. We propose Speculative Lock Elision (SLE), a novel micro-architectural technique to remove dynamically unnecessary lock-induced serialization and enable highly concurrent multithreaded execution. The key insight is that locks do not always have to be acquired for a correct execution. Synchronization instructions are predicted as being unnecessary and elided. This allows multiple threads to concurrently execute critical sections protected by the same lock. Misspeculation due to inter-thread data conflicts is detected using existing cache mechanisms and rollback is used for recovery. Successful speculative elision is validated and committed without acquiring the lock. SLE can be implemented entirely in microarchitecture without instruction set support and without system-level modifications, is transparent to programmers, and requires only trivial additional hardware support. SLE can provide programmers a fast path to writing correct high-performance multithreaded programs.

Concurrency control has been thoroughly studied in the context of traditional database applications such as banking and airline reservations systems. There are relatively few studies, however, that address the concurrency control issues of advanced database applications such as CAD/CAM and software development environments. The

Rover is a software toolkit that supports the construction of both mobile-transparent and mobile-aware appli-cations. The objective of the mobile-transparent approach istodevelop proxies for system services that hide the mobile characteristics of the environment from applications. Since applications can be run without alteration, the mobile-transparent approach is appealing. However, to excel, applications operating in the harsh conditions of a mobile environment must often be aware of and take an active part in mitigating those conditions. The Rover toolkit supports a set of programming and communication abstractions that enable the construction of both mobile-transparent and mobile-aware applications. Using the Rover abstractions, applications obtain increased availability, concurrency, resource allocation e ciency, fault tolerance, consistency, and adaptation. Experimental evaluation of a suite of mobile applications built with the toolkit demonstrates that such application-level control can be obtained with relatively little programming overhead and allows correct operation, increases interactive performance, and dramatically reduces network utilization under intermittently connected conditions. I.

This paper is motivated by the difficulty in writing correct high-performance programs. Writing shared-memory multithreaded programs imposes a complex trade-off between programming ease and performance, largely due to subtleties in coordinating access to shared data. To ensure correctness programmers often rely on conservative locking at the expense of performance. The resulting serialization of threads is a performance bottleneck. Locks also interact poorly with thread scheduling and faults, resulting in poor system performance.

A number of recent studies have examined the performance of concurrency control algorithms for database management systems. The results reported to date, rather than being definitive, have tended to be contradictory. In this paper, rather than presenting “yet another algorithm performance study,” we critically investigate the assumptions made in the models used in past studies and their implica-tions. We employ a fairly complete model of a database environment for studying the relative performance of three different approaches to the concurrency control problem under a variety of modeling assumptions. The three approaches studied represent different extremes in how transaction conflicts are dealt with, and the assumptions addressed pertain to the nature of the database system’s resources, how transaction restarts are modeled, and the amount of information available to the concurrency control algorithm about transactions ’ reference strings. We show that differences in the underlying assumptions explain the seemingly contradictory performance results. We also address the question of how realistic the various assumptions are for actual database systems.

In this paper, we propose a new shared memory model: Transactional

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