Section: New Results

Parallel and Distributed Computing

The scalability of multithreaded applications on current multicore systems is hampered by the performance of lock algorithms, due to the costs of access contention and cache misses. In an article published in ACM Transactions on Computer Systems (TOCS), we present a new locking technique, Remote Core Locking (RCL) [10] , that aims to accelerate the execution of critical sections in legacy applications on multicore architectures. The idea of RCL is to replace lock acquisitions by optimized remote procedure calls to a dedicated server hardware thread. RCL limits the performance collapse observed with other lock algorithms when many threads try to acquire a lock concurrently and removes the need to transfer lock-protected shared data to the hardware thread acquiring the lock because such data can typically remain in the server's cache. Other contributions presented in this article include a profiler that identifies the locks that are the bottlenecks in multithreaded applications and that can thus benefit from RCL, and a reengineering tool that transforms POSIX lock acquisitions into RCL locks. Eighteen applications were used to evaluate RCL: the nine applications of the SPLASH-2 benchmark suite, the seven applications of the Phoenix 2 benchmark suite, Memcached, and Berkeley DB with a TPC-C client. Eight of these applications are unable to scale because of locks and benefit from RCL on an x86 machine with four AMD Opteron processors and 48 hardware threads. By using RCL instead of Linux POSIX locks, performance is improved by up to 2.5 times on Memcached, and up to 11.6 times on Berkeley DB with the TPC-C client. On a SPARC machine with two Sun Ultrasparc T2+ processors and 128 hardware threads, three applications benefit from RCL. In particular, performance is improved by up to 1.3 times with respect to Solaris POSIX locks on Memcached, and up to 7.9 times on Berkeley DB with the TPC-C client.

Software Transactional Memory (STM) is an optimistic concurrency control mechanism that simplifies parallel programming. Still, there has been little interest in its applicability for reactive applications in which there is a required response time for certain operations. In an article published in ACM Transactions on Parallel Computing (TOPC) [11] , we propose supporting such applications by allowing programmers to associate time with atomic blocks in the forms of deadlines and QoS requirements. Based on statistics of past executions, we adjust the execution mode of transactions by decreasing the level of optimism as the deadline approaches. In the presence of concurrent deadlines, we propose different conflict resolution policies. Execution mode switching mechanisms allow meeting multiple deadlines in a consistent manner, with potential QoS degradations being split fairly among several threads as contention increases, and avoiding starvation. Our implementation consists of extensions to a STM runtime that allow gathering statistics and switching execution modes. We also propose novel contention managers adapted to transactional workloads subject to deadlines. The experimental evaluation shows that our approaches significantly improve the likelihood of a transaction meeting its deadline and QoS requirement, even in cases where progress is hampered by conflicts and other concurrent transactions with deadlines.

A challenge in designing a peer-to-peer (P2P) system is to ensure that the system is able to tolerate selfish nodes that strategically deviate from their specification whenever doing so is convenient. In a paper published at SRDS 2015 [13] , we propose RACOON, a framework for the design of P2P systems that are resilient to selfish behaviours. While most existing solutions target specific systems or types of selfishness, RACOON proposes a generic and semi-automatic approach that achieves robust and reusable results. Also, RACOON supports the system designer in the performance-oriented tuning of the system, by proposing a novel approach that combines Game Theory and simulations. We illustrate the benefits of using RACOON by designing two P2P systems: a live streaming and an anonymous communication system. In simulations and a real deployment of the two applications on a testbed comprising 100 nodes, the systems designed using RACOON achieve both resilience to selfish nodes and high performance.