A concurrent object is a data object shared by concurrent processes. Linearizability is a correctness condition for concurrent objects that exploits the semantics of abstract data types. It permits a high degree of concurrency, yet it permits programmers to specify and reason about concurrent objects using known techniques from the sequential domain. Linearizability provides the illusion that each operation applied by concurrent processes takes effect instantaneously at some point between its invocation and its response, implying that the meaning of a concurrent object's operations can be given by pre-and post-conditions. This paper defines linearizability, compares it to other correctness conditions, presents and demonstrates a method for proving the correctness of implementations, and shows how to reason about concurrent objects, given they are linearizable.

A wait-free implementation of a concurrent data object is one that guarantees that any process can complete any operation in a finite number of steps, regardless of the execution speeds of the other processes. The problem of constructing a wait-free implementation of one data object from another lies at the heart of much recent work in concurrent algorithms, concurrent data structures, and multiprocessor architectures. First, we introduce a simple and general technique, based on reduction to a concensus protocol, for proving statements of the form, “there is no wait-free implementation of X by Y.” We derive a hierarchy of objects such that no object at one level has a wait-free implementation in terms of objects at lower levels. In particular, we show that atomic read/write registers, which have been the focus of much recent attention, are at the bottom of the hierarchy: thay cannot be used to construct wait-free implementations of many simple and familiar data types. Moreover, classical synchronization primitives such as test&set and fetch&add , while more powerful than read and write , are also computationally weak, as are the standard message-passing primitives. Second, nevertheless, we show that there do exist simple universal objects from which one can construct a wait-free implementation of any sequential object.

A shared data structure is lock-free if its operations do not require mutual exclusion. If one process is interrupted in the middle of an operation, other processes will not be prevented from operating on that object. In highly con current systems, lock-free data structures avoid common problems associated with conventional locking techniques, including priority inversion, convoying, and difficulty of avoiding deadlock. This paper introduces transactional memory, a new multiprocessor architecture intended to make lock-free synchronization as efficient (and easy to use) as conventional techniques based on mutual exclu sion. Transactional memory allows programmers to de fine customized read-modify-write operations that apply to multiple, independently-chosen words of memory. It is implemented by straightforward extensions to any mul tiprocessor cache-coherence protocol. Simulation results show that transactional memory matches or outperforms the best known locking techniques for simple benchmarks, even in the absence of priority inversion, convoying, and deadlock.

Computer architecture is about to undergo, if not another revolution, then a vigorous shaking-up. The major chip manufacturers have, for the time being, simply given up trying to make processors run faster. Instead, they have recently started shipping "multicore" architectures, in which multiple processors (cores) communicate directly through shared hardware caches, providing increased concurrency instead of increased clock speed.As a result, system designers and software engineers can no longer rely on increasing clock speed to hide software bloat. Instead, they must somehow learn to make effective use of increasing parallelism. This adaptation will not be easy. Conventional synchronization techniques based on locks and conditions are unlikely to be effective in such a demanding environment. Coarse-grained locks, which protect relatively large amounts of data, do not scale, and fine-grained locks introduce substantial software engineering problems.Transactional memory is a computational model in which threads synchronize by optimistic, lock-free transactions. This synchronization model promises to alleviate many (not all) of the problems associated with locking, and there is a growing community of researchers working on both software and hardware support for this approach. This talk will survey the area, with a focus on open research problems.

We propose a new form of software transactional memory (STM) designed to support dynamic-sized data structures, and we describe a novel non-blocking implementation. The non-blocking property we consider is obstruction-~eedom.Obstruction-freedom is weaker than lock-freedom; as a result, it admits substantially simpler and more efficient implementations. A novel feature of our obstruction-free STM implementation is its use of modular contention managers to ensure progress in practice. We illustrate the utility of our dynamic STM with a straightforward implementation of an obstruction-free red-black tree, thereby demonstrating a sophisticated non-blocking dynamic data structure that would be difficult to implement by other means. We also present the results of simple preliminary performance experiments that demonstrate that an "early release" feature of our STM is useful for reducing contention, and that our STM lends itself to the effective use of modular contention managers.

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An atomic cross-chain swap is a distributed coordination task where multiple parties exchange assets across multiple blockchains, for example, trading bitcoin for ether.An atomic swap protocol guarantees (1) if all parties conform to the protocol, then all swaps take place, (2) if some coalition deviates from the protocol, then no conforming party ends up worse o , and (3) no coalition has an incentive to deviate from the protocol.A cross-chain swap is modeled as a directed graph D, whose vertexes are parties and whose arcs are proposed asset transfers. For any pair (D, L), where D = (V , A) is a strongly-connected directed graph and L ⊂ V a feedback vertex set for D, we give an atomic cross-chain swap protocol for D, using a form of hashed timelock contracts, where the vertexes in L generate the hashlocked secrets. We show that no such protocol is possible if D is not strongly connected, or if D is strongly connected but L is not a feedback vertex set. e protocol has time complexity O(diam(D)) and space complexity (bits stored on all blockchains) O(|A| 2 ).