The virtual time machine

Journal ArticleExisting multiprocessors and multicomputers require the programmer or compiler to perform data dependence analysis at compile time. We propose a parallel computer that performs this task at runtime. In particular, the Virtual Time Machine (VTM) detects violations of data dependence constraints as they occur, and automatically recovers from them. A sophisticated memory system that is addressed using both a spatial and a temporal coordinate is used to efficiently implement this mechanism. Initially targeted for discrete event simulation applications, many of the ideas used in the machine architecture have direct application in the more general realm of parallel computation. The long term goal of this work is to develop a general purpose parallel computer that will support a wide range of parallel programming paradigms. This paper outlines the motivations behind the V TM architecture, the underlying computation model, a proposed implementation, and initial performance results. A recurring theme that pervades the entire paper is our contention that existing shared memory and message-base machines do not pay adequate attention to the dimension of time. We argue that this architectural deficiency is the underlying reason behind many difficult problems in parallel computation today

A scalable architecture for ordered parallelism

We present Swarm, a novel architecture that exploits ordered irregular parallelism, which is abundant but hard to mine with current software and hardware techniques. In this architecture, programs consist of short tasks with programmer-specified timestamps. Swarm executes tasks speculatively and out of order, and efficiently speculates thousands of tasks ahead of the earliest active task to uncover ordered parallelism. Swarm builds on prior TLS and HTM schemes, and contributes several new techniques that allow it to scale to large core counts and speculation windows, including a new execution model, speculation-aware hardware task management, selective aborts, and scalable ordered commits. We evaluate Swarm on graph analytics, simulation, and database benchmarks. At 64 cores, Swarm achieves 51--122× speedups over a single-core system, and out-performs software-only parallel algorithms by 3--18×.National Science Foundation (U.S.) (Award CAREER-145299

Semantic definition of a subset of the structured query language (SQL)

Journal ArticleSQL is a relational database definition and manipulation language. Portions of the manipulation language are readily described in terms of relational algebra. The semantics of a subset of the SQL select statement is described. The select statement allows the user to query the database. The select statement is shown to be equivalent to a series of relational and set operations. The semantics are described in terms of abstract data types for relation schemes, tuples, and relations. Certain forms of the union or intersection of two select statements are shown to have equivalent single select statement forms

Building a (virtual) aleph: the visual transformation of a tiny cosmogony

This article discusses the transformation of a tiny three-dimensional artwork created in the metaverse that takes its inspiration from Jorge Luis Borges's story of 'the Aleph' - a tale that revolves around a minute artefact that is 'one of the points in space that contains all other points'. The visualization of a concept as complex as 'the Aleph' led the author of the project through a process that started from Cartesian precepts, from where it transformed itself into an investigation of 'code' as a basal, life-giving presence that is abstract, enigmatic and hermetic in its essence. This correlation between 'code' and the magical nature of 'the Aleph' has led to further considerations regarding the significance of such a marvellous object within virtual worlds. Accordingly, this text will conclude with the description of an intriguing, novel usage for 'the Aleph' that materializes as a time machine for virtual-world avatars

Virtual time synchronization in distributed database systems

Distributed systems synchronized by Virtual Time have been topics of recent interest. Virtual Time follows an optimistic philosophy relying on rollback for synchronization instead of abortion or blocKing Although many applications have been suggested as candidates for Virtual Time, few were simulated or implemented. This research reports on the first implementation and results of a Distributed Database Management System synchronized by virtual time. We argue that virtual time is a viable alternate concurrency control method for distributed database systems if its memory overhead can be absorbed

Parallel simulation techniques for telecommunication network modelling

In this thesis, we consider the application of parallel simulation to the performance modelling of telecommunication networks. A largely automated approach was first explored using a parallelizing compiler to speed up the simulation of simple models of circuit-switched networks. This yielded reasonable results for relatively little effort compared with other approaches. However, more complex simulation models of packet- and cell-based telecommunication networks, requiring the use of discrete event techniques, need an alternative approach. A critical review of parallel discrete event simulation indicated that a distributed model components approach using conservative or optimistic synchronization would be worth exploring. Experiments were therefore conducted using simulation models of queuing networks and Asynchronous Transfer Mode (ATM) networks to explore the potential speed-up possible using this approach. Specifically, it is shown that these techniques can be used successfully to speed-up the execution of useful telecommunication network simulations. A detailed investigation has demonstrated that conservative synchronization performs very well for applications with good look ahead properties and sufficient message traffic density and, given such properties, will significantly outperform optimistic synchronization. Optimistic synchronization, however, gives reasonable speed-up for models with a wider range of such properties and can be optimized for speed-up and memory usage at run time. Thus, it is confirmed as being more generally applicable particularly as model development is somewhat easier than for conservative synchronization. This has to be balanced against the more difficult task of developing and debugging an optimistic synchronization kernel and the application models

Building Scalable Architectures Using Emerging Memory Technologies

A confluence of trends is reshaping computing today. On one end, the massive amounts of data being generated by the proliferation of sensing and internet services are creating a demand for better computer architectures and systems. The other stream of the confluence is the nanotechnology advances that are unearthing new memory device technologies with the potential to replace (or be combined with) conventional memories. Given these trends, this thesis examines emerging memory device technologies that provide a unique opportunity to build computer architectures with efficient and scalable data storage and processing capabilities. The associated memory architectures of these new systems promise to offer distinctive features such as intrinsic non-volatility, highly dense memory structures, extremely low-power consumption and even embedded processing capabilities. Among others, some examples of emerging memory technologies with such features are PCM, 3D Xpoint, STT-RAM and ReRAM. A central question with the new memory architectures built with emerging memory technologies is whether or not the resultant systems are scalable. Towards answering this question, this thesis identifies that conventional memory architecture specific scaling methods may not directly apply in case of emerging memory technologies. These methods were developed mostly for SRAM and DRAM, and today, they do not provide the desired outcomes for emerging memory technologies. As a result, there exist fundamental unsolved problems concerning scalability in building memory architectures. Unfortunately, this means that even though emerging memory technologies provide distinctive features, they may be largely left untapped. Given the scalability concerns, this thesis then advocates a scalability-first approach for building computer architectures using emerging memory technologies while being aware of the limitations and opportunities associated with them. As demonstrations of the scalability-first approach, the thesis discusses several scalability problems encountered in systems using emerging memory technologies. It also brings out potential solutions for each of these problems in the form of novel techniques and tools. For instance, the thesis discusses the problem and a solution for scaling write order enforcement mechanisms for data persistence on large non-volatile main memory systems, followed by the problem and a potential solution for scaling write bandwidth and thereby reducing memory interference on systems with dense non-volatile memory caches. Also discussed are methods for scaling system architectures with in-memory processing capability subject to its operational complexity and other limits. The proposed scalability-first approach points to prospects and ways for better adoption of emerging memory technologies within existing systems. The approach and the solutions also lead to likely transition paths to even more scalable and markedly different systems of the future