220 research outputs found

    Strong Memory Consistency For Parallel Programming

    Get PDF
    Correctly synchronizing multithreaded programs is challenging, and errors can lead to program failures (e.g., atomicity violations). Existing memory consistency models rule out some possible failures, but are limited by depending on subtle programmer-defined locking code and by providing unintuitive semantics for incorrectly synchronized code. Stronger memory consistency models assist programmers by providing them with easier-to-understand semantics with regard to memory access interleavings in parallel code. This dissertation proposes a new strong memory consistency model based on ordering-free regions (OFRs), which are spans of dynamic instructions between consecutive ordering constructs (e.g. barriers). Atomicity over ordering-free regions provides stronger atomicity than existing strong memory consistency models with competitive performance. Ordering-free regions also simplify programmer reasoning by limiting the potential for atomicity violations to fewer points in the program’s execution. This dissertation explores both software-only and hardware-supported systems that provide OFR serializability

    Maintaining consistency in distributed systems

    Get PDF
    In systems designed as assemblies of independently developed components, concurrent access to data or data structures normally arises within individual programs, and is controlled using mutual exclusion constructs, such as semaphores and monitors. Where data is persistent and/or sets of operation are related to one another, transactions or linearizability may be more appropriate. Systems that incorporate cooperative styles of distributed execution often replicate or distribute data within groups of components. In these cases, group oriented consistency properties must be maintained, and tools based on the virtual synchrony execution model greatly simplify the task confronting an application developer. All three styles of distributed computing are likely to be seen in future systems - often, within the same application. This leads us to propose an integrated approach that permits applications that use virtual synchrony with concurrent objects that respect a linearizability constraint, and vice versa. Transactional subsystems are treated as a special case of linearizability

    Safe open-nested transactions through ownership

    Full text link

    Safe Open-Nested Transactions Through Ownership

    Get PDF
    Researchers in transactional memory (TM) have proposed open nesting asa methodology for increasing the concurrency of a program. The ideais to ignore certain "low-level" memory operations of anopen-nested transaction when detecting conflicts for its parenttransaction, and instead perform abstract concurrency control for the"high-level" operation that nested transaction represents. Tosupport this methodology, TM systems use an open-nested commitmechanism that commits all changes performed by an open-nestedtransaction directly to memory, thereby avoiding low-levelconflicts. Unfortunately, because the TM runtime is unaware of thedifferent levels of memory, an unconstrained use of open-nestedcommits can lead to anomalous program behavior.In this paper, we describe a framework of ownership-awaretransactional memory which incorporates the notion of modules into theTM system and requires that transactions and data be associated withspecific transactional modules or Xmodules. We propose a newownership-aware commit mechanism, a hybrid between anopen-nested and closed-nested commit which commits a piece of datadifferently depending on whether the current Xmodule owns the data ornot. Moreover, we give a set of precise constraints on interactionsand sharing of data among the Xmodules based on familiar notions ofabstraction. We prove that ownership-aware TM has has cleanmemory-level semantics and can guarantee serializability bymodules, which is an adaptation of multilevel serializability fromdatabases to TM. In addition, we describe how a programmer canspecify Xmodules and ownership in a Java-like language. Our typesystem can enforce most of the constraints required by ownership-awareTM statically, and can enforce the remaining constraints dynamically.Finally, we prove that if transactions in the process of aborting obeyrestrictions on their memory footprint, the OAT model is free fromsemantic deadlock

    Correctness and Progress Verification of Non-Blocking Programs

    Get PDF
    The progression of multi-core processors has inspired the development of concurrency libraries that guarantee safety and liveness properties of multiprocessor applications. The difficulty of reasoning about safety and liveness properties in a concurrent environment has led to the development of tools to verify that a concurrent data structure meets a correctness condition or progress guarantee. However, these tools possess shortcomings regarding the ability to verify a composition of data structure operations. Additionally, verification techniques for transactional memory evaluate correctness based on low-level read/write histories, which is not applicable to transactional data structures that use a high-level semantic conflict detection. In my dissertation, I present tools for checking the correctness of multiprocessor programs that overcome the limitations of previous correctness verification techniques. Correctness Condition Specification (CCSpec) is the first tool that automatically checks the correctness of a composition of concurrent multi-container operations performed in a non-atomic manner. Transactional Correctness tool for Abstract Data Types (TxC-ADT) is the first tool that can check the correctness of transactional data structures. TxC-ADT elevates the standard definitions of transactional correctness to be in terms of an abstract data type, an essential aspect for checking correctness of transactions that synchronize only for high-level semantic conflicts. Many practical concurrent data structures, transactional data structures, and algorithms to facilitate non-blocking programming all incorporate helping schemes to ensure that an operation comprising multiple atomic steps is completed according to the progress guarantee. The helping scheme introduces additional interference by the active threads in the system to achieve the designed progress guarantee. Previous progress verification techniques do not accommodate loops whose termination is dependent on complex behaviors of the interfering threads, making these approaches unsuitable. My dissertation presents the first progress verification technique for non-blocking algorithms that are dependent on descriptor-based helping mechanisms

    ORCA: Ordering-free Regions for Consistency and Atomicity

    Get PDF
    Writing correct synchronization is one of the main difficulties of multithreaded programming. Incorrect synchronization causes many subtle concurrency errors such as data races and atomicity violations. Previous work has proposed stronger memory consistency models to rule out certain classes of concurrency bugs. However, these approaches are limited by a program’s original (and possibly incorrect) synchronization. In this work, we provide stronger guarantees than previous memory consistency models by punctuating atomicity only at ordering constructs like barriers, but not at lock operations. We describe the Ordering-free Regions for Consistency and Atomicity (ORCA) system which enforces atomicity at the granularity of ordering-free regions (OFRs). While many atomicity violations occur at finer granularity, in an empirical study of many large multithreaded workloads we find no examples of code that requires atomicity coarser than OFRs. Thus, we believe OFRs are a conservative approximation of the atomicity requirements of many programs. ORCA assists programmers by throwing an exception when OFR atomicity is threatened, and, in exception-free executions, guaranteeing that all OFRs execute atomically. In our evaluation, we show that ORCA automatically prevents real concurrency bugs. A user-study of ORCA demonstrates that synchronizing a program with ORCA is easier than using a data race detector. We evaluate modest hardware support that allows ORCA to run with just 18% slowdown on average over pthreads, with very similar scalability
    • …
    corecore