A Compiler and Runtime Infrastructure for Automatic Program Distribution

This paper presents the design and the implementation of a compiler and runtime infrastructure for automatic program distribution. We are building a research infrastructure that enables experimentation with various program partitioning and mapping strategies and the study of automatic distribution's effect on resource consumption (e.g., CPU, memory, communication). Since many optimization techniques are faced with conflicting optimization targets (e.g., memory and communication), we believe that it is important to be able to study their interaction. We present a set of techniques that enable flexible resource modeling and program distribution. These are: dependence analysis, weighted graph partitioning, code and communication generation, and profiling. We have developed these ideas in the context of the Java language. We present in detail the design and implementation of each of the techniques as part of our compiler and runtime infrastructure. Then, we evaluate our design and present preliminary experimental data for each component, as well as for the entire system

An instrumentation tool for threaded Java application servers

Rapid development of e-business services has extended the use of application servers on companies. The Java platform has an important presence on this sector because of its portability and development facilities. Java application servers are becoming a key component in these environments, thus the knowledge of these servers behavior requires the use of new tools to overcome the limitations of existing ones in both offered information and semantics of execution. The natural environment for e-business applications is composed by medium-range parallel servers executing Java based threaded applications. So, understanding threaded Java application servers on parallel environments is the main target of our tool: JIS (Java Instrumentation Suite). This paper describes the design and implementation of JIS and highlights some of the main functionalities. Our initial implementation targets the JVM version 1.3 running Jakarta Tomcat v4.0 on top of a Linux parallel platform with a 2.4.16 kernel.Peer ReviewedPostprint (published version

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

Performance and Interoperability In Solar

Ubiquitous computing promises to integrate computers into our physical environment, surrounding us with applications that are able to adapt to our dynamics. Solar is a software infrastructure designed to deliver contextual information to these applications. To serve the large number and wide variety of context-aware devices envisioned by ubiquitous computing, Solar must exhibit both high performance and the ability to interoperate with many computing platforms. We created a testing framework to measure the performance of distributed systems such as Solar, as well as a pluggable data-transfer mechanism to support the dissemination of information to heterogeneous applications. This paper explores the testing framework developed, analyzes its findings concerning the performance of the current Solar prototype, presents several optimizations to Solar and their effects, and finally discusses the design of the pluggable data-transfer mechanism

Services in pervasive computing environments : from design to delivery

The work presented in this thesis is based on the assumption that modern computer technologies are already potentially pervasive: CPUs are embedded in any sort of device; RAM and storage memory of a modern PDA is comparable to those of a ten years ago Unix workstation; Wi-Fi, GPRS, UMTS are leveraging the development of the wireless Internet. Nevertheless, computing is not pervasive because we do not have a clear conceptual model of the pervasive computer and we have not tools, methodologies, and middleware to write and to seamlessly deliver at once services over a multitude of heterogeneous devices and different delivery contexts. Our thesis addresses these issues starting from the analysis of forces in a pervasive computing environment: user mobility, user profile, user position, and device profile. The conceptual model, or metaphor, we use to drive our work is to consider the environment as surrounded by a multitude of services and objects and devices as the communicating gates between the real world and the virtual dimension of pervasive computing around us. Our thesis is thus built upon three main “pillars”. The first pillar is a domain-object-driven methodology which allows developer to abstract from low level details of the final delivery platform, and provides the user with the ability to access services in a multi-channel way. The rationale is that domain objects are self-contained pieces of software able to represent data and to compute functions and procedures. Our approach fills the gap between users and domain objects building an appropriate user interface which is both adapted to the domain object and to the end user device. As example, we present how to design, implement and deliver an electronic mail application over various platforms. The second pillar of this thesis analyzes in more details the forces that make direct object manipulation inadequate in a pervasive context. These forces are the user profile, the device profile, the context of use, and the combinatorial explosion of domain objects. From the analysis of the electronic mail application presented as example, we notice that according to the end user device, or according to particular circumstances during the access to the service (for instance if the user access the service by the interactive TV while he is having his breakfast) some functionalities are not compulsory and do not fit an adequate task sequence. So we decided to make task models explicit in the design of a service and to integrate the capability to automatically generate user interfaces for domain objects with the formal definition of task models adapted to the final delivery context. Finally, the third pillar of our thesis is about the lifecycle of services in a pervasive computing environment. Our solutions are based upon an existing framework, the Jini connection technology, and enrich this framework with new services and architectures for the deployment and discovery of services, for the user session management, and for the management of offline agents

Enabling aggressive compiler optimization for the mobile environment

Aggressive code optimization on the mobile environment is a difficult endeavor. Billions of users rely on mobile devices for their daily computing tasks. Yet, they mostly run poorly optimized code, under-utilizing their already limited processing and energy resources. Existing optimization approaches, like iterative compilation, perform well in other domains but fall short on the mobile environment. They either rely on representative inputs that are hard to reconstruct, or expose users to slowdowns and crashes. An ideal solution must be able to perform an optimization search by repeatedly evaluating different optimization decisions on the same input. That input should be representative of actual user usage without requiring developers to artificially create it. Finally, users should never be exposed to slow or crashing evaluations, a quite common side-effect of iterative compilation. This thesis presents a novel approach with all above in mind, bringing aggressive code optimization to the mobile environment. With a transparent capture mechanism, real user inputs can be stored. This mechanism is infrequently invoked and remains unnoticeable from the users. A single capture is enough to enable offline, input-driven code optimization. It supports C functions as well as code regions of interactive Android applications. It allows controlling the timing and frequency of captures, it bails out on imminent high-impact runtime events, and excludes from captures some immutable data. A replay-based evaluation mechanism is able to repeatedly restore a captured input while changing the underlying code. For C programs, it employs compile and link-time strategies to consistently work despite code transformations. For Android apps, a novel mechanism was developed, able to replay using different code types. These are the original Android-compiled code, interpretation, and LLVM-generated code. Additionally, it works well even in the presence of memory-shuffling security mechanisms. Capture and replay is fused into an iterative compilation system that uses offline, replay-based evaluations. Initially, real inputs are captured online, without noticeably affecting the users. For C and interactive apps, captures required on average 2ms and 15ms respectively. Then, an optimization search is performed by repeatedly replaying the inputs using different code transformations. As this happens offline, any crashing or erroneous executions are not affecting the users. C programs became 29% faster using a random search, while interactive apps became 44% faster using a genetic algorithm and a novel Android backend based on LLVM. Finally, with crowd-sourcing, the offline evaluation effort was significantly accelerated. Specifically, for the user with the highest workload the search accelerated by 7 times

A DATA MINING-BASED FRAMEWORK TO IDENTIFY SHOPPING MISSIONS

The success of any business depends on the ability to understand its customers. As any other business so do retailers, understanding the reasons consumers enter their stores is playing a key role in achieving competitive advantage and retaining their market shares. Nowadays, the advent of Business Analytics has created new ways for retailers to metamorphose the vast amount of data they have into valuable knowledge, in order to gain customers’ insights, and improve customer relationships. However, not enough research has been conducted to analyze point-of-sale (POS) retail data in order to investigate consumers’ behavior and understand the reasons they visit retail stores. This study presents an effort to fill this gap by introducing a Data Mining-based Framework, which could be used to discover patterns in customers\u27 visits in a supermarket, and identify their Shopping Missions. The utility of this framework is been demonstrated by applying it in real data of eight representative stores of a Greek retailer. The proposed approach is useful for both academia and retail industry. As it gives the retailers the opportunity to extract consumers’ shopping missions when they visit their supermarkets, it could be used to support several decisions in the retail domain, and improve the relationships between retailers and consumers