On-stack replacement, distilled

On-stack replacement (OSR) is essential technology for adaptive optimization, allowing changes to code actively executing in a managed runtime. The engineering aspects of OSR are well-known among VM architects, with several implementations available to date. However, OSR is yet to be explored as a general means to transfer execution between related program versions, which can pave the road to unprecedented applications that stretch beyond VMs. We aim at filling this gap with a constructive and provably correct OSR framework, allowing a class of general-purpose transformation functions to yield a special-purpose replacement. We describe and evaluate an implementation of our technique in LLVM. As a novel application of OSR, we present a feasibility study on debugging of optimized code, showing how our techniques can be used to fix variables holding incorrect values at breakpoints due to optimizations

An input centric paradigm for program dynamic optimizations and lifetime evolvement

Accurately predicting program behaviors (e.g., memory locality, method calling frequency) is fundamental for program optimizations and runtime adaptations. Despite decades of remarkable progress, prior studies have not systematically exploited the use of program inputs, a deciding factor of program behaviors, to help in program dynamic optimizations. Triggered by the strong and predictive correlations between program inputs and program behaviors that recent studies have uncovered, the dissertation work aims to bring program inputs into the focus of program behavior analysis and program dynamic optimization, cultivating a new paradigm named input-centric program behavior analysis and dynamic optimization.;The new optimization paradigm consists of three components, forming a three-layer pyramid. at the base is program input characterization, a component for resolving the complexity in program raw inputs and extracting important features. In the middle is input-behavior modeling, a component for recognizing and modeling the correlations between characterized input features and program behaviors. These two components constitute input-centric program behavior analysis, which (ideally) is able to predict the large-scope behaviors of a program\u27s execution as soon as the execution starts. The top layer is input-centric adaptation, which capitalizes on the novel opportunities created by the first two components to facilitate proactive adaptation for program optimizations.;This dissertation aims to develop this paradigm in two stages. In the first stage, we concentrate on exploring the implications of program inputs for program behaviors and dynamic optimization. We construct the basic input-centric optimization framework based on of line training to realize the basic functionalities of the three major components of the paradigm. For the second stage, we focus on making the paradigm practical by addressing multi-facet issues in handling input complexities, transparent training data collection, predictive model evolvement across production runs. The techniques proposed in this stage together cultivate a lifelong continuous optimization scheme with cross-input adaptivity.;Fundamentally the new optimization paradigm provides a brand new solution for program dynamic optimization. The techniques proposed in the dissertation together resolve the adaptivity-proactivity dilemma that has been limiting the effectiveness of existing optimization techniques. its benefits are demonstrated through proactive dynamic optimizations in Jikes RVM and version selection using IBM XL C Compiler, yielding significant performance improvement on a set of Java and C/C++ programs. It may open new opportunities for a broad range of runtime optimizations and adaptations. The evaluation results on both Java and C/C++ applications demonstrate the new paradigm is promising in advancing the current state of program optimizations

Profile-directed specialisation of custom floating-point hardware

We present a methodology for generating floating-point arithmetic hardware designs which are, for suitable applications, much reduced in size, while still retaining performance and IEEE-754 compliance. Our system uses three key parts: a profiling tool, a set of customisable floating-point units and a selection of system integration methods. We use a profiling tool for floating-point behaviour to identify arithmetic operations where fundamental elements of IEEE-754 floating-point may be compromised, without generating erroneous results in the common case. In the uncommon case, we use simple detection logic to determine when operands lie outside the range of capabilities of the optimised hardware. Out-of-range operations are handled by a separate, fully capable, floatingpoint implementation, either on-chip or by returning calculations to a host processor. We present methods of system integration to achieve this errorcorrection. Thus the system suffers no compromise in IEEE-754 compliance, even when the synthesised hardware would generate erroneous results. In particular, we identify from input operands the shift amounts required for input operand alignment and post-operation normalisation. For operations where these are small, we synthesise hardware with reduced-size barrel-shifters. We also propose optimisations to take advantage of other profile-exposed behaviours, including removing the hardware required to swap operands in a floating-point adder or subtractor, and reducing the exponent range to fit observed values. We present profiling results for a range of applications, including a selection of computational science programs, Spec FP 95 benchmarks and the FFMPEG media processing tool, indicating which would be amenable to our method. Selected applications which demonstrate potential for optimisation are then taken through to a hardware implementation. We show up to a 45% decrease in hardware size for a floating-point datapath, with a correctable error-rate of less then 3%, even with non-profiled datasets

ReferralWeb--a resource location system guided by personal relations

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (p. 47-[48]).by Mehul A. ShahM.Eng

Dynamic Binary Translation for Embedded Systems with Scratchpad Memory

Embedded software development has recently changed with advances in computing. Rather than fully co-designing software and hardware to perform a relatively simple task, nowadays embedded and mobile devices are designed as a platform where multiple applications can be run, new applications can be added, and existing applications can be updated. In this scenario, traditional constraints in embedded systems design (i.e., performance, memory and energy consumption and real-time guarantees) are more difficult to address. New concerns (e.g., security) have become important and increase software complexity as well. In general-purpose systems, Dynamic Binary Translation (DBT) has been used to address these issues with services such as Just-In-Time (JIT) compilation, dynamic optimization, virtualization, power management and code security. In embedded systems, however, DBT is not usually employed due to performance, memory and power overhead. This dissertation presents StrataX, a low-overhead DBT framework for embedded systems. StrataX addresses the challenges faced by DBT in embedded systems using novel techniques. To reduce DBT overhead, StrataX loads code from NAND-Flash storage and translates it into a Scratchpad Memory (SPM), a software-managed on-chip SRAM with limited capacity. SPM has similar access latency as a hardware cache, but consumes less power and chip area. StrataX manages SPM as a software instruction cache, and employs victim compression and pinning to reduce retranslation cost and capture frequently executed code in the SPM. To prevent performance loss due to excessive code expansion, StrataX minimizes the amount of code inserted by DBT to maintain control of program execution. When a hardware instruction cache is available, StrataX dynamically partitions translated code among the SPM and main memory. With these techniques, StrataX has low performance overhead relative to native execution for MiBench programs. Further, it simplifies embedded software and hardware design by operating transparently to applications without any special hardware support. StrataX achieves sufficiently low overhead to make it feasible to use DBT in embedded systems to address important design goals and requirements

Software tools for real-time simulation and control

The objective of this thesis is to design and simulate a multi-agent based energy management system for a shipboard power system in hard real-time environment. The automatic reconfiguration of shipboard power systems is essential to improve survivability. Multi-agent technology is used in designing the reconfigurable energy management system using a self-stabilizing maximum flow algorithm. The agent based energy management system is designed in a Matlab/Simulink environment. Reconfiguration is performed for several situations including start-up, loss of an agent, limited available power, and distribution to priority ranked loads. The number of steps taken to reach the global solution and the time taken are very promising. With the growing importance of timing accuracy in simulating control systems during design and development, there is an increased need for these simulations to run in a real-time environment. This research further focuses on software tools that support hard real-time environment to run real-time simulations. A detailed survey has been conducted on freely available real-time operating systems and other software tools to setup a desktop PC supporting real-time environment. Matlab/Simulink/RTW-RTAI was selected as real-time computer aided control design software for demonstrating real-time simulation of agent based energy management system. The timing accuracy of these simulations has been verified successfully

Co-Evolution of Source Code and the Build System: Impact on the Introduction of AOSD in Legacy Systems

Software is omnipresent in our daily lives. As users demand ever more advanced features, software systems have to keep on evolving. In practice, this means that software developers need to adapt the description of a software application. Such a description not only consists of source code written down in a programming language, as a lot of knowledge is hidden in lesser known software development artifacts, like the build system. As its name suggests, the build system is responsible for building an executable program, ready for use, from the source code. There are various indications that the evolution of source code is strongly related to that of the build system. When the source code changes, the build system has to co-evolve to safeguard the ability to build an executable program. A rigid build system on the other hand limits software developers. This phenomenon especially surfaces when drastic changes in the source code are coupled with an inflexible build system, as is the case for the introduction of AOSD technology in legacy systems. AOSD is a young software development approach which enables developers to structure and compose source code in a better way. Legacy systems are old software systems which are still mission-critical, but of which the source code and the build system are no longer fully understood, and which typically make use of old(-fashioned) technology. This PhD dissertation focuses on finding an explanation for this co-evolution of source code and the build system, and on finding developer support to grasp and manage this phenomenon. We postulate four "roots of co-evolution" which represent four different ways in which source code and the build system interact with each other. Based on these roots, we have developed tool and aspect language support to understand and manage co-evolution. The roots and the tool support have been validated in case studies, both in the context of co-evolution in general and of the introduction of AOSD technology in legacy systems. The dissertation experimentally shows that co-evolution indeed is a real problem, but that specific software development and aspect language support enables developers to deal with it