Adjacency lists are frequently used in graphing or map based applications. Although efficient concurrent linked-list algorithms are well known, it can be difficult to adapt these approaches to build a high-performance adjacency list. Furthermore, it can often be desirable to execute operations in these data structures transactionally, or perform a sequence of operations in one atomic step. In this paper, we present a lock-free transactional adjacency list based on a multi-dimensional list (MDList). We are able to combine known linked list strategies with the capability of the MDList in order to efficiently organize graph vertexes and their edges. We design our underlying data structure to be node-based and linearizable, then use the Lock-Free Transactional Transformation (LFTT) methodology to efficiently enable transactional execution. In our performance evaluation, our lock-free transactional adjacency list achieves an average of 50 speedup over a transactional boosting implementation.
@cite_4 presented a transactional skiplist that uses STM-like techniques combined with node locking in an attempt to reduce overhead and false aborts. additionally present a transactional queue using a pessimistic lock-based approach. In this queue, the execution of operations are deferred to the final phase of the transaction, the commit phase, in order to avoid keeping track of the current head of the queue. Meanwhile, operations acquire a lock on the queue until their transaction is complete. Zhang and Dechev @cite_26 preserved lock-freedom in their algorithm by transforming a skiplist using LFTT which, again, offers a performance improvement on transaction rollbacks.
@cite_26 @cite_4
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As we learn from the literature, flexibility in choosing synchronization operations greatly simplifies the task of designing highly concurrent programs. Unfortunately, existing hardware is inflexible and is at best on the level of a Load–Linked Store–Conditional operation on a single word. Building on the hardware based transactional synchronization methodology of Herlihy and Moss, we offer software transactional memory (STM), a novel software method for supporting flexible transactional programming of synchronization operations. STM is non-blocking, and can be implemented on existing machines using only a Load–Linked Store–Conditional operation. We use STM to provide a general highly concurrent method for translating sequential object implementations to non-blocking ones based on implementing a k-word compare&swap STM-transaction. Empirical evidence collected on simulated multiprocessor architectures shows that our method always outperforms the non-blocking translation methods in the style of Barnes, and outperforms Herlihy’s translation method for sufficiently large numbers of processors. The key to the efficiency of our software-transactional approach is that unlike Barnes style methods, it is not based on a costly “recursive helping” policy. Transactional Lock Elision (TLE) uses Hardware Transactional Memory (HTM) to execute unmodified critical sections concurrently, even if they are protected by the same lock. To ensure correctness, the transactions used to execute these critical sections “subscribe” to the lock by reading it and checking that it is available. A recent paper proposed using the tempting “lazy subscription” optimization for a similar technique in a different context, namely transactional systems that use a single global lock (SGL) to protect all transactional data. We identify several pitfalls that show that lazy subscription is not safe for TLE because unmodified critical sections executing before subscribing to the lock may behave incorrectly in a number of subtle ways. We also show that recently proposed compiler support for modifying transaction code to ensure subscription occurs before any incorrect behavior could manifest is not sufficient to avoid all of the pitfalls we identify. We further argue that extending such compiler support to avoid all pitfalls would add substantial complexity and would usually limit the extent to which subscription can be deferred, undermining the effectiveness of the optimization. Hardware extensions suggested in the recent proposal also do not address all of the pitfalls we identify. A longer version of this paper proposes hardware extensions that make lazy subscription safe, both for SGL-based transactional systems and for TLE, without the need for special compiler support.