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128
Treadmarks: Shared memory computing on networks of workstations
- Computer
, 1996
"... TreadMarks supports parallel computing on networks of workstations by providing the application with a shared memory abstraction. Shared memory facilitates the transition from sequential to parallel programs. After identifying possible sources of parallelism in the code, most of the data structures ..."
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Cited by 484 (37 self)
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TreadMarks supports parallel computing on networks of workstations by providing the application with a shared memory abstraction. Shared memory facilitates the transition from sequential to parallel programs. After identifying possible sources of parallelism in the code, most of the data structures can be retained without change, and only synchronization needs to be added to achieve a correct shared memory parallel program. Additional transformations may be necessary to optimize performance, but this can be done in an incremental fashion. We discuss the techniques used in TreadMarks to provide e cient shared memory, and our experience with two large applications, mixed integer programming and genetic linkage analysis. 1
Evaluation of Release Consistent Software Distributed Shared Memory on Emerging Network Technology
"... We evaluate the effect of processor speed, network characteristics, and software overhead on the performance of release-consistent software distributed shared memory. We examine five different protocols for implementing release consistency: eager update, eager invalidate, lazy update, lazy invalidat ..."
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Cited by 468 (43 self)
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We evaluate the effect of processor speed, network characteristics, and software overhead on the performance of release-consistent software distributed shared memory. We examine five different protocols for implementing release consistency: eager update, eager invalidate, lazy update, lazy invalidate, and a new protocol called lazy hybrid. This lazy hybrid protocol combines the benefits of both lazy update and lazy invalidate. Our simulations indicate that with the processors and networks that are becoming available, coarse-grained applications such as Jacobi and TSP perform well, more or less independent of the protocol used. Medium-grained applications, such as Water, can achieve good performance, but the choice of protocol is critical. For sixteen processors, the best protocol, lazy hybrid, performed more than three times better than the worst, the eager update. Fine-grained applications such as Cholesky achieve little speedup regardless of the protocol used because of the frequency of synchronization operations and the high latency involved. While the use of relaxed memory models, lazy implementations, and multiple-writer protocols has reduced the impact of false sharing, synchronization latency remains a serious problem for software distributed shared memory systems. These results suggest that future work on software DSMs should concentrate on reducing the amount ofsynchronization or its effect.
Shared memory consistency models: A tutorial
- IEEE Computer
, 1996
"... Parallel systems that support the shared memory abstraction are becoming widely accepted in many areas of computing. Writing correct and efficient programs for such systems requires a formal specification of memory semantics, called a memory consistency model. The most intuitive model—sequential con ..."
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Cited by 435 (11 self)
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Parallel systems that support the shared memory abstraction are becoming widely accepted in many areas of computing. Writing correct and efficient programs for such systems requires a formal specification of memory semantics, called a memory consistency model. The most intuitive model—sequential consistency—greatly restricts the use of many performance optimizations commonly used by uniprocessor hardware and compiler designers, thereby reducing the benefit of using a multiprocessor. To alleviate this problem, many current multiprocessors support more relaxed consistency models. Unfortunately, the models supported by various systems differ from each other in subtle yet important ways. Furthermore, precisely defining the semantics of each model often leads to complex specifications that are difficult to understand for typical users and builders of computer systems. The purpose of this tutorial paper is to describe issues related to memory consistency models in a way that would be understandable to most computer professionals. We focus on consistency models proposed for hardware-based shared-memory systems. Many of these models are originally specified with an emphasis on the system optimizations they allow. We retain the system-centric emphasis, but use uniform and simple terminology to describe the different models. We also briefly discuss an alternate programmer-centric view that describes the models in terms of program behavior rather than specific system optimizations. 1
Fixing the Java memory model
- In ACM Java Grande Conference
, 1999
"... This paper describes the new Java memory model, which has been revised as part of Java 5.0. The model specifies the legal behaviors for a multithreaded program; it defines the semantics of multithreaded Java programs and partially determines legal implementations of Java virtual machines and compile ..."
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Cited by 381 (11 self)
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This paper describes the new Java memory model, which has been revised as part of Java 5.0. The model specifies the legal behaviors for a multithreaded program; it defines the semantics of multithreaded Java programs and partially determines legal implementations of Java virtual machines and compilers. The new Java model provides a simple interface for correctly synchronized programs – it guarantees sequential consistency to data-race-free programs. Its novel contribution is requiring that the behavior of incorrectly synchronized programs be bounded by a well defined notion of causality. The causality requirement is strong enough to respect the safety and security properties of Java and weak enough to allow standard compiler and hardware optimizations. To our knowledge, other models are either too weak because they do not provide for sufficient safety/security, or are too strong because they rely on a strong notion of data and control dependences that precludes some standard compiler transformations. Although the majority of what is currently done in compilers is legal, the new model introduces significant differences, and clearly defines the boundaries of legal transformations. For example, the commonly accepted definition for control dependence is incorrect for Java, and transformations based on it may be invalid. In addition to providing the official memory model for Java, we believe the model described here could prove to be a useful basis for other programming languages that currently lack well-defined models, such as C++ and C#.
Job Scheduling in Multiprogrammed Parallel Systems
, 1997
"... Scheduling in the context of parallel systems is often thought of in terms of assigning tasks in a program to processors, so as to minimize the makespan. This formulation assumes that the processors are dedicated to the program in question. But when the parallel system is shared by a number of us ..."
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Cited by 176 (16 self)
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Scheduling in the context of parallel systems is often thought of in terms of assigning tasks in a program to processors, so as to minimize the makespan. This formulation assumes that the processors are dedicated to the program in question. But when the parallel system is shared by a number of users, this is not necessarily the case. In the context of multiprogrammed parallel machines, scheduling refers to the execution of threads from competing programs. This is an operating system issue, involved with resource allocation, not a program development issue. Scheduling schemes for multiprogrammed parallel systems can be classified as one or two leveled. Single-level scheduling combines the allocation of processing power with the decision of which thread will use it. Two level scheduling decouples the two issues: first, processors are allocated to the job, and then the job's threads are scheduled using this pool of processors. The processors of a parallel system can be shared i...
The Multiscalar Architecture
, 1993
"... The centerpiece of this thesis is a new processing paradigm for exploiting instruction level parallelism. This paradigm, called the multiscalar paradigm, splits the program into many smaller tasks, and exploits fine-grain parallelism by executing multiple, possibly (control and/or data) depen-dent t ..."
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Cited by 124 (8 self)
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The centerpiece of this thesis is a new processing paradigm for exploiting instruction level parallelism. This paradigm, called the multiscalar paradigm, splits the program into many smaller tasks, and exploits fine-grain parallelism by executing multiple, possibly (control and/or data) depen-dent tasks in parallel using multiple processing elements. Splitting the instruction stream at statically determined boundaries allows the compiler to pass substantial information about the tasks to the hardware. The processing paradigm can be viewed as extensions of the superscalar and multiprocess-ing paradigms, and shares a number of properties of the sequential processing model and the dataflow processing model. The multiscalar paradigm is easily realizable, and we describe an implementation of the multis-calar paradigm, called the multiscalar processor. The central idea here is to connect multiple sequen-tial processors, in a decoupled and decentralized manner, to achieve overall multiple issue. The mul-tiscalar processor supports speculative execution, allows arbitrary dynamic code motion (facilitated by an efficient hardware memory disambiguation mechanism), exploits communication localities, and does all of these with hardware that is fairly straightforward to build. Other desirable aspects of the
Causal Memory: Definitions, Implementation and Programming
, 1994
"... The abstraction of a shared memory is of growing importance in distributed computing systems. Traditional memory consistency ensures that all processes agree on a common order of all operations on memory. Unfortunately, providing these guarantees entails access latencies that prevent scaling to larg ..."
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Cited by 122 (9 self)
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The abstraction of a shared memory is of growing importance in distributed computing systems. Traditional memory consistency ensures that all processes agree on a common order of all operations on memory. Unfortunately, providing these guarantees entails access latencies that prevent scaling to large systems. This paper weakens such guarantees by defining causal memory, an abstraction that ensures that processes in a system agree on the relative ordering of operations that are causally related. Because causal memory is weakly consistent, it admits more executions, and hence more concurrency, than either atomic or sequentially consistent memories. This paper provides a formal definition of causal memory and gives an implementation for message-passing systems. In addition, it describes a practical class of programs that, if developed for a strongly consistent memory, run correctly with causal memory. College of Computing Georgia Institute of Technology Atlanta, Georgia 30332-0280 This ...
Software Write Detection for a Distributed Shared Memory
- IN PROCEEDINGS OF THE FIRST USENIX SYMPOSIUM ON OPERATING SYSTEM DESIGN AND IMPLEMENTATION
, 1994
"... Most software-based distributed shared memory (DSM) systems rely on the operating system's virtual memory interface to detect writes to shared data. Strategies based on virtual memory page protection create two problems for a DSM system. First, writes can have high overhead since they are detec ..."
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Cited by 105 (0 self)
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Most software-based distributed shared memory (DSM) systems rely on the operating system's virtual memory interface to detect writes to shared data. Strategies based on virtual memory page protection create two problems for a DSM system. First, writes can have high overhead since they are detected with a page fault. As a result, a page must be writtenmany times to amortize the cost of that fault. Second, the size of a virtual memory page is too big to serve as a unit of coherency, inducing false sharing. Mechanisms to handle false sharing can increase runtime overhead and may cause data to be unnecessarily communicated between processors. In this paper, we present a new method for write detection that solves these problems. Our method relies on the compiler and runtime system to detect writes to shared data without invoking the operating system. We measure and compare implementations of a distributed shared memory system using both strategies, virtual memory and compiler /runtime, run...
Speculative Synchronization: Applying Thread-Level Speculation to Explicitly Parallel Applications
- ASPLOS X
, 2002
"... Barriers, locks, and flags are synchronizing operations widely used by programmers and parallelizing compilers to produce race-free parallel programs. Often times, these operations are placed suboptimally, either because of conservative assumptions about the program, or merely for code simplicity. W ..."
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Cited by 94 (7 self)
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Barriers, locks, and flags are synchronizing operations widely used by programmers and parallelizing compilers to produce race-free parallel programs. Often times, these operations are placed suboptimally, either because of conservative assumptions about the program, or merely for code simplicity. We propose
x86-TSO: A Rigorous and Usable Programmer’s Model for x86 Multiprocessors
"... Exploiting the multiprocessors that have recently become ubiquitous requires high-performance and reliable concurrent systems code, for concurrent data structures, operating system kernels, synchronisation libraries, compilers, and so on. However, concurrent programming, which is always challenging, ..."
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Cited by 79 (7 self)
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Exploiting the multiprocessors that have recently become ubiquitous requires high-performance and reliable concurrent systems code, for concurrent data structures, operating system kernels, synchronisation libraries, compilers, and so on. However, concurrent programming, which is always challenging, is made much more so by two problems. First, realmultiprocessorstypicallydonotprovidethesequentially consistent memory that is assumed by most work on semantics and verification. Instead, they have relaxed memory models, varying in subtle ways between processor families, in which different hardware threads may have only loosely consistent views of a shared memory. Second, the public vendor architectures, supposedly specifying what programmers can rely on, are often in ambiguous informal prose (a particularly poor medium for loose specifications), leading to widespread confusion. In this paper we focus on x86 processors. We review several recent Intel and AMD specifications, showing that all contain serious ambiguities, some are arguably too weak to program above, and some are simply unsound with respect to actual hardware. We present a new x86-TSO programmer’s model that, to the best of our knowledge, suffers from none of these problems. It is mathematically precise (rigorously defined in HOL4) but can be presented as an intuitive abstract machine which should be widely accessible to working programmers. We illustrate how this can be used to reason about the correctness of a Linux spinlock implementationanddescribeageneraltheoryofdata-race-freedomfor x86-TSO. This should put x86 multiprocessor system building on a more solid foundation; it should also provide a basis for future work on verification of such systems. 1.
