Compiler‐driven approach for automating nonblocking synchronization in concurrent data abstractions

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.

Transactional memory (TM) has been the focus of numerous studies, and it is supported in processors such as the IBM Blue Gene/Q and Intel Haswell. Many studies have used the STAMP benchmark suite to evaluate their designs. However, the speedups obtained for the STAMP benchmarks on all TM systems we know of are quite limited; for example, with 64 threads on the IBM Blue Gene/Q, we observe a median speedup of 1.4X using the Blue Gene/Q hardware transactional memory (HTM), and a median speedup of 4.1X using a software transactional memory (STM). What limits the performance of these benchmarks on TMs? In this paper, we argue that the problem lies with the programming model and data structures used to write them. To make this point, we articulate two principles that we believe must be embodied in any scalable program and argue that STAMP programs violate both of them. By modifying the STAMP programs to satisfy both principles, we produce a new set of programs that we call the Stampede suite. Its median speedup on the Blue Gene/Q is 8.0X when using an STM. The two principles also permit us to simplify the TM design. Using this new STM with the Stampede benchmarks, we obtain a median speedup of 17.7X with 64 threads on the Blue Gene/Q and 13.2X with 32 threads on an Intel Westmere system. These results suggest that HTM and STM designs will benefit if more attention is paid to the division of labor between application programs, systems software, and hardware.

Software transactional memory (STM) is a promising technique for controlling concurrency in modern multi-processor architectures. STM aims to be more scalable than explicit coarse-grained locking and easier to use than fine-grained locking. However, STM implementations have yet to demonstrate that their runtime overheads are acceptable. To date, empiric evaluations of these implementations have suffered from the lack of realistic benchmarks. Measuring performance of an STM in an overly simplified setting can be at best uninformative and at worst misleading as it may steer researchers to try to optimize irrelevant aspects of their implementations. This paper presents STMBench7: a candidate benchmark for evaluating STM implementations. The underlying data structure consists of a set of graphs and indexes intended to be suggestive of many complex applications, e.g., CAD/CAM. A collection of operations is supported to model a wide range of workloads and concurrency patterns. Companion locking strategies serve as a baseline for STM performance comparisons. STMBench7 strives for simplicity. Users may choose a workload, number of threads, benchmark length, as well as the possibility of structure modification and the nature of traversals of shared data structures. We illustrate the use of STMBench7 with an evaluation of a well-known software transactional memory implementation.

This paper introduces nonblocking transaction composition (NBTC), a new methodology for atomic composition of nonblocking operations on concurrent data structures. Unlike previous software transactional memory (STM) approaches, NBTC leverages the linearizability of existing nonblocking structures, reducing the number of memory accesses that must be executed together, atomically, to only one per operation in most cases (these are typically the linearizing instructions of the constituent operations).

Simplified parallel programming coupled with an ability to express speculative computation is realized with Software Transactional Memory (STM). Although STMs are gaining popularity because of significant improvements in parallel performance, they exhibit enormous variation in transaction execution with non-repeatable performance behavior which is unacceptable in many application domains, especially in which frame rates and responsiveness should be predictable. Thus, reducing execution variance in STM is an important performance goal that has been mostly overlooked. In this work, we minimize the variance in execution time of threads in STM by reducing non-determinism exhibited due to speculation by first quantifying non-determinism and generating an automaton that models the behavior of STM. We used the automaton to guide the STM to a less non-deterministic execution that reduced the variance in frame rate by a maximum of 65% on a version of real-world Quake3 game.

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.

Software Transactional Memory (STM) algorithms provide programmers with a high-level synchronization technique for concurrent programming. STMs guarantee “seemingly atomic” access to shared state via transactions. This seeming atomicity is the standard requirement on STM implementations and formalized in the concept of opacity. The standard proof technique for opacity is via refinement: the STM implementation is shown to refine an IO automaton called TMS2 which itself is known to be opaque.

Much research has been done in the area of software transactional memory (STM) as a new programming paradigm to help ease the implementation of parallel applications. While most research has been invested for answering the question of how STM should be implemented, there is less work about how to use STM efficiently. This paper is focused on the challenge of how to use STM for efficient and scalable implementations of non-trivial applications. We present a fine-grained STM-based concurrent binary heap, an application of STM for a data structure that is notoriously difficult to parallelize. We describe extensions to the basic STM approach and also the benefits of our proposal. Our results show that the fine-grained STM-based binary heap provides very good scalability compared to the naive approach. Nevertheless, we reach a point where the complexity of some fine-grained techniques do not justify its use for the increase in performance that can be obtained.

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.

The recent architectural trend that has lead to the widespread adoption of multi-core CPUs has fostered a remarkable research interest in Software Transactional Memory (STM). As STMs are starting to face the high availability and scalability requirements of real-world production environments, it is natural to foresee the need for replication solutions specifically tailored for STMs. Since databases and STMs share the same key abstraction of atomic transaction, one could wonder whether the mechanisms originally designed for database replication could be successfully and seamlessly exploited also to support replication of STM systems.This paper seeks an answer to this question, highlighting some critical performance issues related to the application of state of the art database replication techniques in the context of STM systems, and presenting some of our recent research directions aimed at designing and implementing high performance replication strategies able to meet the unique requirements of STMs.

Software Transactional Memory (STM) is a powerful tool for managing access to shared data. A major impairment to the adoption of this technology in mainstream applications is the lack of efficient replication schemes capable of ensuring adequate scalability and fault-tolerance levels. A key issue is that no existing replication approach succeeds in delivering optimal performance across the entire spectrum of possible transactional workloads.In this work we describe an architecture for generic replication of STMs. Our approach strongly simplifies the development and evaluation of alternative STM replication policies, by defining neat, generic interfaces that encapsulate the three key components at the core of a replicated STM: the local STM, the replica coordination manager and the underlying group communication system. Our generic architecture for STM replication aims at integrating the results from the growing community of researchers working in this area, paving the way towards the development of self-optimizing STM replication mechanisms.

Virtual world consistency: A condition for STM systems (with a versatile protocol with invisible read operations)

© 2017 by John Wiley & Sons, Inc. All rights reserved. Concurrent data structures are the data sharing side of parallel programming. An implementation of a data structure is called lock-free, if it allows multiple processes/hreads to access the data structure concurrently and also guarantees that at least one operation among those finishes in a finite number of its own steps regardless of the state of the other operations. This chapter provides a sufficient background and intuition to help the interested reader to navigate in the complex research area of lock-free data structures. It offers the programmer familiarity to the subject that allows using truly concurrent methods. The chapter discusses the fundamental synchronization primitives on which efficient lock-free data structures rely. It discusses the problem of managing dynamically allocated memory in lock-free concurrent data structures and general concurrent environments. The idiosyncratic architectural features of graphics processors that is important to consider when designing efficient lock-free concurrent data structures for this emerging area.

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.

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%.