Transaction Activation scheduling Support for Transactional Memory

Transactional Memory (TM) is considered as one of the most promising paradigms for developing concurrent applications. TM has been shown to scale well on multiple cores when the data access pattern behaves “well,” i.e., when few conflicts are induced. In contrast, data patterns with frequent write sharing, with long transactions, or when many threads contend for a smaller number of cores, produce numerous aborts. These problems are traditionally addressed by application-level contention managers, but they suffer from a lack of precision and provide unpredictable benefits on many workloads. In this paper, we propose a system approach where the scheduler tries to avoid aborts by preventing conflicting transactions from running simultaneously. We use a combination of several techniques to help reduce the odds of conflicts, by (1) avoiding preempting threads running a transaction until the transaction completes, (2) keeping track of conflicts and delaying the restart of a transaction until conflicting transactions have committed, and (3) keeping track of conflicts and only allowing a thread with conflicts to run at low priority. Our approach has been implemented in Linux for Software Transactional Memory (STM) using a shared memory segment to allow fast communication between the STM library and the scheduler. It only requires small and contained modifications to the operating system. Experimental evaluation demonstrates that our approach significantly reduces the number of aborts while improving transaction throughput on various workloads

Scheduling in Transactional Memory Systems: Models, Algorithms, and Evaluations

Transactional memory provides an alternative synchronization mechanism that removes many limitations of traditional lock-based synchronization so that concurrent program writing is easier than lock-based code in modern multicore architectures. The fundamental module in a transactional memory system is the transaction which represents a sequence of read and write operations that are performed atomically to a set of shared resources; transactions may conflict if they access the same shared resources. A transaction scheduling algorithm is used to handle these transaction conflicts and schedule appropriately the transactions. In this dissertation, we study transaction scheduling problem in several systems that differ through the variation of the intra-core communication cost in accessing shared resources. Symmetric communication costs imply tightly-coupled systems, asymmetric communication costs imply large-scale distributed systems, and partially asymmetric communication costs imply non-uniform memory access systems. We made several theoretical contributions providing tight, near-tight, and/or impossibility results on three different performance evaluation metrics: execution time, communication cost, and load, for any transaction scheduling algorithm. We then complement these theoretical results by experimental evaluations, whenever possible, showing their benefits in practical scenarios. To the best of our knowledge, the contributions of this dissertation are either the first of their kind or significant improvements over the best previously known results

On the Impact of Memory Allocation on High-Performance Query Processing

Somewhat surprisingly, the behavior of analytical query engines is crucially affected by the dynamic memory allocator used. Memory allocators highly influence performance, scalability, memory efficiency and memory fairness to other processes. In this work, we provide the first comprehensive experimental analysis on the impact of memory allocation for high-performance query engines. We test five state-of-the-art dynamic memory allocators and discuss their strengths and weaknesses within our DBMS. The right allocator can increase the performance of TPC-DS (SF 100) by 2.7x on a 4-socket Intel Xeon server

Dynamic Prediction based Scheduling for TM

Transactional memory (TM) provides an intuitive and simple way of writing parallel programs. TMs execute parallel programs speculatively and deliver better performance than conventional lock based parallel programs. However, in certain scenarios when an application lacks scope for parallelism, TMs are outperformed by conventional fine-grained locking. TM schedulers, which serialize transactions that face contention, have shown promise in improving performance of TMs in such scenarios. In this thesis, we develop a Dynamic Prediction based Scheduler (DPS) that exploits novel prediction techniques, like temporal locality and locality of access across repeated transactions. DPS predicts the access sets of future transactions based on the access patterns of the past transactions of the individual threads. We also propose a novel heuristic, called serialization affinity, which tends to serialize transactions with a probability proportional to the current amount of contention. Using the information of the currently executing transactions, the current amount of contention, and the predicted access sets, DPS dynamically serializes transactions to minimize conflicts. We implement DPS in two state-of-the-art STMs, SwissTM and TinySTM. Our results show that in scenarios where the number of threads is higher than the number of cores, DPS improves the performance of these STMs by up to 55% and 3000% respectively. On the other hand, the overhead of prediction techniques in DPS causes a performance degradation of just 5-8% in some cases, when the number of threads is less than the number of cores

Contention management for distributed data replication

PhD ThesisOptimistic replication schemes provide distributed applications with access to shared data at lower latencies and greater availability. This is achieved by allowing clients to replicate shared data and execute actions locally. A consequence of this scheme raises issues regarding shared data consistency. Sometimes an action executed by a client may result in shared data that may conflict and, as a consequence, may conflict with subsequent actions that are caused by the conflicting action. This requires a client to rollback to the action that caused the conflicting data, and to execute some exception handling. This can be achieved by relying on the application layer to either ignore or handle shared data inconsistencies when they are discovered during the reconciliation phase of an optimistic protocol. Inconsistency of shared data has an impact on the causality relationship across client actions. In protocol design, it is desirable to preserve the property of causality between different actions occurring across a distributed application. Without application level knowledge, we assume an action causes all the subsequent actions at the same client. With application knowledge, we can significantly ease the protocol burden of provisioning causal ordering, as we can identify which actions do not cause other actions (even if they precede them). This, in turn, makes possible the client’s ability to rollback to past actions and to change them, without having to alter subsequent actions. Unfortunately, increased instances of application level causal relations between actions lead to a significant overhead in protocol. Therefore, minimizing the rollback associated with conflicting actions, while preserving causality, is seen as desirable for lower exception handling in the application layer. In this thesis, we present a framework that utilizes causality to create a scheduler that can inform a contention management scheme to reduce the rollback associated with the conflicting access of shared data. Our framework uses a backoff contention management scheme to provide causality preserving for those optimistic replication systems with high causality requirements, without the need for application layer knowledge. We present experiments which demonstrate that our framework reduces clients’ rollback and, more importantly, that the overall throughput of the system is improved when the contention management is used with applications that require causality to be preserved across all actions

Tailoring Transactional Memory to Real-World Applications

Transactional Memory (TM) promises to provide a scalable mechanism for synchronizationin concurrent programs, and to offer ease-of-use benefits to programmers. Since multiprocessorarchitectures have dominated CPU design, exploiting parallelism in program

A speculative execution approach to provide semantically aware contention management for concurrent systems

PhD ThesisMost modern platforms offer ample potention for parallel execution of concurrent programs yet concurrency control is required to exploit parallelism while maintaining program correctness. Pessimistic con- currency control featuring blocking synchronization and mutual ex- clusion, has given way to transactional memory, which allows the composition of concurrent code in a manner more intuitive for the application programmer. An important component in any transactional memory technique however is the policy for resolving conflicts on shared data, commonly referred to as the contention management policy. In this thesis, a Universal Construction is described which provides contention management for software transactional memory. The technique differs from existing approaches given that multiple execution paths are explored speculatively and in parallel. In the resolution of conflicts by state space exploration, we demonstrate that both concur- rent conflicts and semantic conflicts can be solved, promoting multi- threaded program progression. We de ne a model of computation called Many Systems, which defines the execution of concurrent threads as a state space management problem. An implementation is then presented based on concepts from the model, and we extend the implementation to incorporate nested transactions. Results are provided which compare the performance of our approach with an established contention management policy, under varying degrees of concurrent and semantic conflicts. Finally, we provide performance results from a number of search strategies, when nested transactions are introduced

Performance Optimization Strategies for Transactional Memory Applications

This thesis presents tools for Transactional Memory (TM) applications that cover multiple TM systems (Software, Hardware, and hybrid TM) and use information of all different layers of the TM software stack. Therefore, this thesis addresses a number of challenges to extract static information, information about the run time behavior, and expert-level knowledge to develop these new methods and strategies for the optimization of TM applications

Software lock elision for x86 machine code

More than a decade after becoming a topic of intense research there is no transactional memory hardware nor any examples of software transactional memory use outside the research community. Using software transactional memory in large pieces of software needs copious source code annotations and often means that standard compilers and debuggers can no longer be used. At the same time, overheads associated with software transactional memory fail to motivate programmers to expend the needed effort to use software transactional memory. The only way around the overheads in the case of general unmanaged code is the anticipated availability of hardware support. On the other hand, architects are unwilling to devote power and area budgets in mainstream microprocessors to hardware transactional memory, pointing to transactional memory being a "niche" programming construct. A deadlock has thus ensued that is blocking transactional memory use and experimentation in the mainstream. This dissertation covers the design and construction of a software transactional memory runtime system called SLE_x86 that can potentially break this deadlock by decoupling transactional memory from programs using it. Unlike most other STM designs, the core design principle is transparency rather than performance. SLE_x86 operates at the level of x86 machine code, thereby becoming immediately applicable to binaries for the popular x86 architecture. The only requirement is that the binary synchronise using known locking constructs or calls such as those in Pthreads or OpenMP libraries. SLE_x86 provides speculative lock elision (SLE) entirely in software, executing critical sections in the binary using transactional memory. Optionally, the critical sections can also be executed without using transactions by acquiring the protecting lock. The dissertation makes a careful analysis of the impact on performance due to the demands of the x86 memory consistency model and the need to transparently instrument x86 machine code. It shows that both of these problems can be overcome to reach a reasonable level of performance, where transparent software transactional memory can perform better than a lock. SLE_x86 can ensure that programs are ready for transactional memory in any form, without being explicitly written for it

Dynamic contention management for distributed applications

PhD ThesisDistributed applications often make use of replicated state to afford a greater level of availability and throughput. This is achieved by allowing individual processes to progress without requiring prior synchronisation. This approach, termed optimistic replication, results in divergent replicas that must be reconciled to achieve an overall consistent state. Concurrent operations to shared objects in the replicas result in conflicting updates that require reconciliatory action to rectify. This typically takes the form of compensatory execution or simply undoing and rolling back client state. When considering user interaction with the application, there exists relationships and intent in the ordering and execution of these operations. The enactment of reconciliation that determines one action as conflicted may have far reaching implications with regards to the user’s original intent. In such scenarios, the compensatory action applied to a conflict may require previous operations to also be undone or compensated such that the user’s intent is maintained. Therefore, an ability to manage the contention to the shared data across the distributed application to pre-emptively lower conflicts resulting from these infringements is desirable. The aim is to not hinder throughput, achieved from the weaker consistency model known as eventual consistency. In this thesis, a model is presented for a contention management framework that schedules access using the expected execution inherent in the application domain to best inform the contention manager. A backoff scheme is employed to create an access schedule, preserving user intent for applications that require this high level of maintenance for user actions. By using such an approach, this results in a performance improvement seen in the reduction of the overall number of conflicts, while also improving overall system throughput. This thesis describes how the contention management scheme operates and, through experimentation, the performance benefits received