What Scalable Programs Need from Transactional Memory

Transactional Memory (TM) has been the promising parallel programming technique to relieve the tedious work of synchronizing shared object using lock mechanism. Transaction execution required to be atomic and isolated relative to the whole system. The transaction fails if found violated access to the shared object from other transaction, and it will be re-executed till finally commit successfully; currently, most TM systems are required to restore shared memory's state before reexecution, this cleanup cost and the shared object's opening cost greatly hurdle system's performance. In this paper, we propose a new general transaction iteration's data reusing (TItDR) method which reuses the opened object of failed transaction in the following re-execution. The obvious advantage is that it greatly simplify the opening process if it has been opened in previous failed transaction and most of the cleanup work are no longer needed. TItDR leaves opened object in pseudo-active state and restart the transaction, We talk about conflicts resolution, validation, commit/abort processing problem along with our data reusing method and show that TItDR will not incur more conflicts and more overhead for validation or commit. Both currently proposed software transactional memory (STM) systems and hardware systems (HTM) have much potential data reusing. Our test result is based on STM implementation, which shows 40% performance improvement on average.

With the advent of Transactional Memory, a multitude of Software Transactional Memory (STM) systems evolved. Often, the programmer sets key parameters of an STM system at compile time. The performance of the application depends on choosing the right parameters. Unfortunately, programmers do not always know the application characteristic to decide on a profound basis. As a consequence, the application may run longer than necessary. Thus, we propose MAPT, which uses static information to guide the programmer to select an STM property. In particular, MAPT assists the programmer to select the resolution of the conflict detection scheme. This paper presents MAPT, its integration in the Low Level Virtual Machine compiler framework, and results from the evaluation with test cases and two STAMP benchmarks.

Software testing is hard. The emergence of multicore architectures and the proliferation of bug-prone multithreaded software makes testing even harder. To this end, researchers have proposed methods to continue testing software after deployment, e.g., in vivo (IV) testing and delta execution (DE) patch testing. These on-line techniques typically fork new processes to hide the functional impact of testing. Unfortunately, the high overhead of fork() significantly degrades performance. To reduce the performance overhead of online testing, we adapt transactional memory (TM) to isolate the functional effects of tests with minimal impact on system performance. We propose StealthTest, an interface that exposes TM transactions as the key mechanism for executing tests. It allows online tests to work on a consistent view of memory without the overhead of creating new processes. Moreover, explicitly aborting the test transaction after it is done guarantees that its changes are invisible to the rest of the system. Thus, StealthTest promises transparent online testing. We demonstrate two test frameworks utilizing StealthTest - StealthlV and StealthDE - that improve on previously proposed fork-based in vivo testing and delta execution frameworks respectively. Implementing StealthTest on top of three software TM (STM) systems - TL2 STM, Intel STM and a pin-based STM- we demonstrate that StealthTest-based frameworks can (a) run a wide range of online tests and (b) execute many more tests with low overhead. StealthTest provides another motivation for efficient TM implementations by extending TM's applicability to a critical software engineering challenge.

Atomic sections are supported in software through the use of optimistic concurrency by using Software Transactional Memory (STM). However STM implementations incur high overheads which reduce the wide-spread use of this approach by programmers. Conflicts are a major source of overheads in STMs. The basic performance premise of a transactional memory system is the optimistic concurrency principle wherein data updates executed by the transactions are to disjoint objects/memory locations, referred to as Disjoint Access Parallel (DAP). Otherwise, the updates conflict, and all but one of the transactions are aborted. Such aborts result in wasted work and performance degradation. While contention management systems in STM implementations try to reduce conflicts by various runtime feedback control mechanisms, they are not aware of the application's structure and data access patterns and hence typically act after the conflicts have occurred. In this paper we propose a scheme based on compiler analysis, which can identify static atomic sections whose instances, when executed concurrently by more than one thread always conflict. Such an atomic section is referred to as Always Conflicting Atomic Section (ACAS). We propose and evaluate two techniques Selective Pessimistic Concurrency Control (SPCC) and compiler inserted Early Conflict Checks (ECC) which can help reduce the STM overheads caused by ACAS. We show that these techniques help reduce the aborts in 4 of the STAMP benchmarks by up to 27.52% while improving performance by 1.24% to 19.31%.

Transactional memory (TM) promises to simplify concurrent programming while providing scalability competitive to fine-grained locking. Language-based constructs allow programmers to denote atomic regions declaratively and to rely on the underlying system to provide transactional guarantees along with concurrency. In contrast with fine-grained locking, TM allows programmers to write simpler programs that are composable and deadlock-free.TM implementations operate by tracking loads and stores to memory and by detecting concurrent conflicting accesses by different transactions. By automating this process, they greatly reduce the programmer's burden, but they also are forced to be conservative. Incertain cases, conflicting memory accesses may not actually violate the higher-level semantics of a program, and a programmer may wish to allow seemingly conflicting transactions to execute concurrently.Open nested transactions enable expert programmers to differentiate between physical conflicts, at the level of memory, and logical conflicts that actually violate application semantics. A TMsystem with open nesting can permit physical conflicts that are not logical conflicts, and thus increase concurrency among application threads.Here we present an implementation of open nested transactions in a Java-based software transactional memory (STM)system. We describe new language constructs to support open nesting in Java, and we discuss new abstract locking mechanisms that a programmer can use to prevent logical conflicts. We demonstrate how these constructs can be mapped efficiently to existing STM data structures. Finally, we evaluate our system on a set of Java applications and data structures, demonstrating how open nesting can enhance application scalability.

The advent of multi-core architectures has brought concurrent programming to the forefront of software development. In this context, Transactional Memory (TM) has gained increasing popularity as a simpler, attractive alternative to traditional lock-based synchronization. The recent integration of Hardware TM (HTM) in the last generation of Intel commodity processors turned TM into a mainstream technology, raising a number of questions on its future and that of concurrent programming. To evaluate the potential impact of Intel's HTM, we conducted the largest study on TM to date, comparing different locking techniques, hardware and software TMs, as well as different combinations of these mechanisms, from the dual perspective of performance and power consumption. As a result we perform a workload characterization, to help programmers better exploit the currently available TM facilities, and identify important research directions.

This paper describes an end-to-end system implementation of the transactional memory (TM) programming model on top of the hardware transactional memory (HTM) of the Blue Gene/Q (BG/Q) machine. The TM programming model supports most C/C++ programming constructs on top of a best-effort HTM with the help of a complete software stack including the compiler, the kernel, and the TM runtime. An extensive evaluation of the STAMP benchmarks on BG/Q is the first of its kind in understanding characteristics of running coarse-grained TM workloads on HTMs. The study reveals several interesting insights on the overhead and the scalability of BG/Q HTM with respect to sequential execution, coarse-grain locking, and software TM.

The transactional memory programming paradigm is gaining momentum as the approach of choice for replacing locks in concurrent programming. This paper introduces the transactional locking II (TL2) algorithm, a software transactional memory (STM) algorithm based on a combination of commit-time locking and a novel global version-clock based validation technique. TL2 improves on state-of-the-art STMs in the following ways: (1) unlike all other STMs it fits seamlessly with any system’s memory life-cycle, including those using malloc/free (2) unlike all other lock-based STMs it efficiently avoids periods of unsafe execution, that is, using its novel version-clock validation, user code is guaranteed to operate only on consistent memory states, and (3) in a sequence of high performance benchmarks, while providing these new properties, it delivered overall performance comparable to (and in many cases better than) that of all former STM algorithms, both lock-based and non-blocking. Perhaps more importantly, on various benchmarks, TL2 delivers performance that is competitive with the best hand-crafted fine-grained concurrent structures. Specifically, it is ten-fold faster than a single lock. We believe these characteristics make TL2 a viable candidate for deployment of transactional memory today, long before hardware transactional support is available.

Drawing inspiration from several previous projects, we present an ownership-record-free software transactional memory (STM) system that combines extremely low overhead with unusually clean semantics. While unlikely to scale to hundreds of active threads, this system offers many appealing features: very low fast-path latency--as low as any system we know of that admits concurrent updates; publication and privatization safety; livelock freedom; a small, constant amount of global metadata, and full compatibility with existing data structure layouts; no false conflicts due to hash collisions; compatibility with both managed and unmanaged languages, and both static and dynamic compilation; and easy acccommodation of closed nesting, inevitable (irrevocable) transactions, and starvation avoidance mechanisms. To the best of our knowledge, no extant STM system combines this set of features.While transactional memory for processors with hundreds of cores is likely to require hardware support, software implementations will be required for backward compatibility with current and near-future processors with 2--64 cores, as well as for fall-back in future machines when hardware resources are exhausted. Our experience suggests that NOrec may be an ideal candidate for such a software system. We also observe that it has considerable appeal for use within the operating system, and in systems that require both closed nesting and publication safety.

Drawing inspiration from several previous projects, we present an ownership-record-free software transactional memory (STM) system that combines extremely low overhead with unusually clean semantics. While unlikely to scale to hundreds of active threads, this "NOrec" system offers many appealing features: very low fast-path latency--as low as any system we know of that admits concurrent updates; publication and privatization safety; livelock freedom; a small, constant amount of global metadata, and full compatibility with existing data structure layouts; no false conflicts due to hash collisions; compatibility with both managed and unmanaged languages, and both static and dynamic compilation; and easy acccommodation of closed nesting, inevitable (irrevocable) transactions, and starvation avoidance mechanisms. To the best of our knowledge, no extant STM system combines this set of features. While transactional memory for processors with hundreds of cores is likely to require hardware support, software implementations will be required for backward compatibility with current and near-future processors with 2--64 cores, as well as for fall-back in future machines when hardware resources are exhausted. Our experience suggests that NOrec may be an ideal candidate for such a software system. We also observe that it has considerable appeal for use within the operating system, and in systems that require both closed nesting and publication safety.

ReduxSTM: Optimizing STM designs for Irregular Applications

With the availability of multicore and manycore systems with large main memories, Symmetric Multiprocessors (SMPs) can process large scale problems such as graphs spanning millions of nodes and billions of edges which used to be the domain of large clusters. Due to the shared memory architecture of SMPs, we can apply fast, novel policies such as Transactional Memory (TM) to speed up the processing of such problems. Interestingly, most applications in bioinformatics, social networks, and cybersecurity can be represented as large graphs. However, these graphs are sparse in nature. Therefore, TM as a synchronization policy for critical sections can provide better performance since it performs better in low conflict scenarios. Many TM variants exist including: Software, Hardware and combinations of both. Furthermore, a TM can adapt to applications' behavior. In this paper, we introduce DAdHTM. A Dynamically Adaptive Hardware TM (DAdHTM) designed to adapt the HTM to the application's behavior. DAdHTM outperforms not only locks but also low overhead Software TM (STM) and even Adaptive Hybrid TM (DyAdHyTM) on a 48 core 64GB memory dual socket SMP machine. Our experiments show that DAdHTM has low overhead. It is competitive at core/thread counts below 24 (close to the best) and outperforms all other techniques at core/thread counts above 24 by up to 43%.

Deterministic execution of a multithreaded application guarantees the same output as long as the application runs with the same input parameters. Determinism helps a programmer to test and debug an application and to provide fault-tolerance in the systems based on replicas. Additionally, Transactional Memory (TM) greatly simplifies development of multithreaded applications where applications use transactions (instead of locks) as a concurrency control mechanism to synchronize accesses to shared memory. However, deterministic systems proposed so far are not TM-aware. They violate the main properties of TM (atomicity, consistency and isolation of transactions), and execute TM applications incorrectly. In this paper, we present DeTrans, a runtime system for deterministic execution of multithreaded TM applications. DeTrans executes TM applications deterministically, it executes nontransactional code serially in round-robin order, and transactional code in parallel. Also, we show how DeTrans works with both eager and lazy software TM. We compare DeTrans with Dthreads, a state-of-the-art deterministic execution system. Unlike Dthreads, DeTrans does not use memory protection hardware nor facilities of the underlying operating system (OS) to execute multithreaded applications deterministically. DeTrans uses properties of software TM to ensure deterministic execution. We evaluate DeTrans using the STAMP benchmark suite and we compare DeTrans and Dthreads performance costs. DeTrans incurs less overhead because threads execute in the same address space without any OS system calls overhead. According to our results, DeTrans is 3.99x, 3.39x, 2.44x faster on average than Dthreads for 2, 4 and 8 threads, respectively.

Conflict detection and resolution are among the most fundamental issues in transactional memory systems. Hardware transactional memory (HTM) systems such as AMD's Advanced Synchronization Facility (ASF) employ inherent cache coherence protocol messages to perform conflict detection among transactions. Such an implementation has the advantage of design simplicity, nonetheless, it also generates false transactional conflicts due to false sharing within cache lines, unnecessarily reducing the overall performance. In this work, we first investigated the behavior of false transactional conflicts under the AMD's ASF system. It is found that false conflicts showed rather stable pattern within each cache line that subsequently inspired our false transactional conflict reduction technique using our proposed speculative sub-blocking state. By adding an extra speculative state for each cache line's sub-block, we can maintain conflict detection at the granularity of sub-blocks while keeping the original cache coherence protocol intact. The overall design is simple and highly implementable for achieving a high-efficiency HTM system with minimum impact in hardware. We evaluated our proposed technique using PTLsim-ASF and compared it with a baseline ASF HTM system and an ideal system with no false transactional conflict. Our results showed that the proposed lightweight technique can avoid false conflicts effectively and efficiently. With four sub-blocks in a cache line, our technique can eliminate 56.4% false transactional conflicts and 31.3% of all transactional conflicts on average, which approaches the performance of an ideal system.

Software Transactional Memory (STM) implementations typically instrument each memory access within transactions with a call to an STM barrier to ensure the correctness of the transactions. Compared to simple memory accesses, STM barriers are complex operations that add significant overhead to transactions doing many memory accesses. Thus, whereas STMs have shown good results for micro-benchmarks, where transactions are small, they often show poor performance on real-world—sized benchmarks, where transactions are more coarse-grained and, therefore, encompass more memory accesses. In this paper, we propose a new runtime technique for lightweight identification of captured memory–LICM–for which no STM barriers are needed. Our technique is independent of the specific STM design and can be used by any STM implemented in a managed environment. We implemented it on the Deuce STM Framework, for three different STMs, and tested it across a variety of benchmarks. Using our technique to remove useless barriers, we improved the performance of all baseline STMs for most benchmarks, with speedups of up to 27 times. Most importantly, we were able to improve the performance of some of the benchmarks, when using an STM, to values close to or better than the performance of the best lock-based approaches.