Transactional Memory (TM) is emerging as a promising technology to simplify parallel programming. While several TM systems have been proposed in the research literature, we are still missing the tools and workloads necessary to analyze and compare the proposals. Most TM systems have been evaluated using microbenchmarks, which may not be representative of any real-world behavior, or individual applications, which do not stress a wide range of execution scenarios. We introduce the Stanford Transactional Application for Multi-Processing (STAMP), a comprehensive benchmark suite for evaluating TM systems. STAMP includes eight applications and thirty variants of input parameters and data sets in order to represent several application domains and cover a wide range of transactional execution cases (frequent or rare use of transactions, large or small transactions, high or low contention, etc.). Moreover, STAMP is portable across many types of TM systems, including hardware, software, and hybrid systems. In this paper, we provide descriptions and a detailed characterization of the applications in STAMP. We also use the suite to evaluate six different TM systems, identify their shortcomings, and motivate further research on their performance characteristics.

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STAMP: Stanford Transactional Applications for Multi-Processing

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 systems 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.

Transactional locking II

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.

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Persistent, user-defined objects present an attractive abstraction for working with non-volatile program state. However, the slow speed of persistent storage (i.e., disk) has restricted their design and limited their performance. Fast, byte-addressable, non-volatile technologies, such as phase change memory, will remove this constraint and allow programmers to build high-performance, persistent data structures in non-volatile storage that is almost as fast as DRAM. Creating these data structures requires a system that is lightweight enough to expose the performance of the underlying memories but also ensures safety in the presence of application and system failures by avoiding familiar bugs such as dangling pointers, multiple free()s, and locking errors. In addition, the system must prevent new types of hard-to-find pointer safety bugs that only arise with persistent objects. These bugs are especially dangerous since any corruption they cause will be permanent.We have implemented a lightweight, high-performance persistent object system called NV-heaps that provides transactional semantics while preventing these errors and providing a model for persistence that is easy to use and reason about. We implement search trees, hash tables, sparse graphs, and arrays using NV-heaps, BerkeleyDB, and Stasis. Our results show that NV-heap performance scales with thread count and that data structures implemented using NV-heaps out-perform BerkeleyDB and Stasis implementations by 32x and 244x, respectively, by avoiding the operating system and minimizing other software overheads. We also quantify the cost of enforcing the safety guarantees that NV-heaps provide and measure the costs of NV-heap primitive operations.

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NV-Heaps: making persistent objects fast and safe with next-generation, non-volatile memories

Transactional memory (TM) simplifies parallel programming by guaranteeing that transactions appear to execute atomically and in isolation. Implementing these properties includes providing data version management for the simultaneous storage of both new (visible if the transaction commits) and old (retained if the transaction aborts) values. Most (hardware) TM systems leave old values "in place" (the target memory address) and buffer new values elsewhere until commit. This makes aborts fast, but penalizes (the much more frequent) commits. In this paper, we present a new implementation of transactional memory, log-based transactional memory (LogTM), that makes commits fast by storing old values to a per-thread log in cacheable virtual memory and storing new values in place. LogTM makes two additional contributions. First, LogTM extends a MOESI directory protocol to enable both fast conflict detection on evicted blocks and fast commit (using lazy cleanup). Second, LogTM handles aborts in (library) software with little performance penalty. Evaluations running micro- and SPLASH-2 benchmarks on a 32-way multiprocessor support our decision to optimize for commit by showing that only 1-2% of transactions abort.

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LogTM: log-based transactional memory

Software Transactional Memory (STM) is a generic synchronization construct that enables automatic conversion of correct sequential objects into correct nonblocking concurrent objects. Recent STM systems, though significantly more practical than their predecessors, display inconsistent performance: differing design decisions cause different systems to perform best in different circumstances, often by dramatic margins. In this paper we consider four dimensions of the STM design space: (i) when concurrent objects are acquired by transactions for modification; (ii) how they are acquired; (iii) what they look like when not acquired; and (iv) the non-blocking semantics for transactions (lock-freedom vs. obstruction-freedom). In this 4-dimensional space we highlight the locations of two leading STM systems: the DSTM of Herlihy et al. and the OSTM of Fraser and Harris. Drawing motivation from the performance of a series of application benchmarks, we then present a new Adaptive STM (ASTM) system that adjusts to the offered workload, allowing it to match the performance of the best known existing system on every tested workload.

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Adaptive software transactional memory

Recent years have seen the development of several dierent systems for software transactional memory (STM). Most either employ locks in the underlying implementation or depend on thread-safe general-purpose garbage collection to collect stale data and metadata. We consider the design of low-overhead, obstruction-free software transactional memory for non-garbage-collected languages. Our design eliminates dynamic allocation of transactional metadata and co-locates data that are separate in other systems, thereby reducing the expected number of cache misses on the common-case code path, while preserving nonblocking progress and requiring no atomic instructions other than single-word load, store, and compare-and-swap (or load-linked/store-conditional). We also employ a simple, epoch-based storage management system and introduce a novel conservative mechanism to make reader transactions visible to writers without inducing additional metadata copying or dynamic allocation. Experimental results show throughput significantly higher than that of existing nonblocking STM systems, and highlight significant, application-specific dierences among conflict detection and validation strategies.

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Lowering the Overhead of Nonblocking Software Transactional Memory

Early implementations of software transactional memory (STM) assumed that sharable data would be accessed only within transactions. Memory may appear inconsistent in programs that violate this assumption, even when program logic would seem to make extra-transactional accesses safe. Designing STM systems that avoid such inconsistency has been dubbed the privatization problem. We argue that privatization comprises a pair of symmetric subproblems: private operations may fail to see updates made by transactions that have committed but not yet completed; conversely, transactions that are doomed but have not yet aborted may see updates made by private code, causing them to perform erroneous, externally visible operations. We explain how these problems arise in different styles of STM, present strategies to address them, and discuss their implementation tradeoffs. We also propose a taxonomy of contracts between the system and the user, analogous to programmer-centric memory consistency models, which allow us to classify programs based on their privatization requirements. Finally, we present empirical comparisons of several privatization strategies. Our results suggest that the best strategy may depend on application characteristics.

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Privatization techniques for software transactional memory

Lowering the Overhead of Software Transactional Memory

In a software transactional memory (STM) system, conflict detection is the problem of determining when two transactions cannot both safely commit. Validation is the related problem of ensuring that a transaction never views inconsistent data, which might potentially cause a doomed transaction to exhibit irreversible, externally visible side effects. Existing mechanisms for conflict detection vary greatly in their degree of speculation and their relative treatment of read-write and write-write conflicts. Validation, for its part, appears to be a dominant factor-perhaps the dominant factor-in the cost of complex transactions. We present the most comprehensive study to date of conflict detection strategies, characterizing the tradeoffs among them and identifying the ones that perform the best for various types of workload. In the process we introduce a lightweight heuristic mechanism-the global commit counter-that can greatly reduce the cost of validation and of single-threaded execution. The heuristic also allows us to experiment with mixed invalidation, a more opportunistic interleaving of reading and writing transactions. Experimental results on a 16-processor SunFire machine running our RSTM system indicate that the choice of conflict detection strategy can have a dramatic impact on performance, and that the best choice is workload dependent. In workloads whose transactions rarely conflict, the commit counter does little to help (and can even hurt) performance. For less scalable applications, however-those in which STM performance has traditionally been most problematic-it can improve transaction throughput many fold.

Virendra J. Marathe

Papers

Adaptive software transactional memory

Lowering the Overhead of Nonblocking Software Transactional Memory

Privatization techniques for software transactional memory

Lowering the Overhead of Software Transactional Memory

Conflict detection and validation strategies for software tradsacfional memory