Macroservers: An Execution Model for DRAM Processor-In-Memory Arrays

The emergence of semiconductor fabrication technology allowing a tight coupling between high-density DRAM and CMOS logic on the same chip has led to the important new class of Processor-In-Memory (PIM) architectures. Newer developments provide powerful parallel processing capabilities on the chip, exploiting the facility to load wide words in single memory accesses and supporting complex address manipulations in the memory. Furthermore, large arrays of PIMs can be arranged into a massively parallel architecture. In this report, we describe an object-based programming model based on the notion of a macroserver. Macroservers encapsulate a set of variables and methods; threads, spawned by the activation of methods, operate asynchronously on the variables' state space. Data distributions provide a mechanism for mapping large data structures across the memory region of a macroserver, while work distributions allow explicit control of bindings between threads and data. Both data and work distributuions are first-class objects of the model, supporting the dynamic management of data and threads in memory. This offers the flexibility required for fully exploiting the processing power and memory bandwidth of a PIM array, in particular for irregular and adaptive applications. Thread synchronization is based on atomic methods, condition variables, and futures. A special type of lightweight macroserver allows the formulation of flexible scheduling strategies for the access to resources, using a monitor-like mechanism

Design of testbed and emulation tools

The research summarized was concerned with the design of testbed and emulation tools suitable to assist in projecting, with reasonable accuracy, the expected performance of highly concurrent computing systems on large, complete applications. Such testbed and emulation tools are intended for the eventual use of those exploring new concurrent system architectures and organizations, either as users or as designers of such systems. While a range of alternatives was considered, a software based set of hierarchical tools was chosen to provide maximum flexibility, to ease in moving to new computers as technology improves and to take advantage of the inherent reliability and availability of commercially available computing systems

Exploring Dynamic Compilation and Cross-Layer Object Management Policies for Managed Language Applications

Recent years have witnessed the widespread adoption of managed programming languages that are designed to execute on virtual machines. Virtual machine architectures provide several powerful software engineering advantages over statically compiled binaries, such as portable program representations, additional safety guarantees, automatic memory and thread management, and dynamic program composition, which have largely driven their success. To support and facilitate the use of these features, virtual machines implement a number of services that adaptively manage and optimize application behavior during execution. Such runtime services often require tradeoffs between efficiency and effectiveness, and different policies can have major implications on the system's performance and energy requirements. In this work, we extensively explore policies for the two runtime services that are most important for achieving performance and energy efficiency: dynamic (or Just-In-Time (JIT)) compilation and memory management. First, we examine the properties of single-tier and multi-tier JIT compilation policies in order to find strategies that realize the best program performance for existing and future machines. Our analysis performs hundreds of experiments with different compiler aggressiveness and optimization levels to evaluate the performance impact of varying if and when methods are compiled. We later investigate the issue of how to optimize program regions to maximize performance in JIT compilation environments. For this study, we conduct a thorough analysis of the behavior of optimization phases in our dynamic compiler, and construct a custom experimental framework to determine the performance limits of phase selection during dynamic compilation. Next, we explore innovative memory management strategies to improve energy efficiency in the memory subsystem. We propose and develop a novel cross-layer approach to memory management that integrates information and analysis in the VM with fine-grained management of memory resources in the operating system. Using custom as well as standard benchmark workloads, we perform detailed evaluation that demonstrates the energy-saving potential of our approach. We implement and evaluate all of our studies using the industry-standard Oracle HotSpot Java Virtual Machine to ensure that our conclusions are supported by widely-used, state-of-the-art runtime technology