物件導向軟體之架構(Object-Oriented Software Construction)探討

[서평]「Component Software」 - Beyond Object-Oriented Programming -

Microsoft has promoted ASP.NET’s new web services more than almost any other part of the.NET Framework. But despite their efforts, confusion is still widespread about what a web service is and, more importantly, what it’s meant to accomplish. This chapter introduces web services and explains their role in Microsoft’s vision of the programmable web. Along the way, you’ll learn about the open standards plumbing that allows web services to work and removes some of the confusion surrounding technical terms like WSDL (Web Service Description Language), SOAP, and UDDI (universal description, discovery, and integration).

Web Services Architecture

for MIMD Distributed-Memory Machines :llel computing resents the only :usible way to continue to increase the computational power available to scientists and engineers. Parallel computers , however, are not likely to be widely successful until they are easy to program. A major component in the success of vector supercomputers is the ability of scientists to write Fortran programs in a "'vec-torizable'" style and expect vectorizing compilers to automatically produce efficient code [8, 35]. The resulting programs are easily maintained , debugged, and ported across different vector machines. Compare this with the current situation for programming parallel machines. Scientists wishing to use such machines must rewrite their programs in an extension of For-tran that explicitly reflects the architecture of the underlying machine. Multiple-instruction, multiple data (MIMD) shared-memory machines such as the Cray Research Y-MP C90 are programmed with explicit synchronization and parallel loops found in Parallel Computing Forum (PCF) Fortran [24]. (SIMD) machines such as the Thinking Machines CM-2 are programmed using parallel array constructs found in Fortran 90 [3]. MIMD distributed-memory machines such as the Intel Paragon provide the most difficult programming model. Users must write message passing Fortran 77 programs that deal with separate address spaces, synchronizing processors, and communicating data using messages. The process is time-consuming, tedious, and error-prone. Significant increases in source code size are not only common but expected. Because parallel programs are extremely machine-specific, scientists are discouraged from utilizing parallel machines because they risk losing their investment whenever the program changes or a new architecture arrives. We propose to solve this problem by developing the compiler technology needed to establish a machine-independent programming model. It must be easy to use, yet perform with acceptable efficiency on different parallel architectures, at least for data-parallel scientific codes. The question is whether any existing Fortran dialect suffices. Parallel Computing Fortran is undesirable because it is easy to inadvertently write programs with data races that produce indeterminate results. Message-passing For-tran 77 is portable, but difficult to use. Fortran 90 is promising, but may not be sufficiently flexible. What all these languages lack is a way to specify the decomposition and placement of data in the program. We find that selecting a data decomposition is one of the most important intellectual steps in developing data-parallel scientific codes. Though many techniques have been developed for automatic data decomposition, we feel that the compiler will not be able to choose an efficient …

Compiling Fortran D for MIMD distributed-memory machines

We survey parallel programming models and languages using six criteria to assess their suitability for realistic portable parallel programming. We argue that an ideal model should by easy to program, should have a software development methodology, should be architecture-independent, should be easy to understand, should guarantee performance, and should provide accurate information about the cost of programs. These criteria reflect our belief that developments in parallelism must be driven by a parallel software industry based on portability and efficiency. We consider programming models in six categories, depending on the level of abstraction they provide. Those that are very abstract conceal even the presence of parallelism at the software level. Such models make software easy to build and port, but efficient and predictable performance is usually hard to achieve. At the other end of the spectrum, low-level models make all of the messy issues of parallel programming explicit (how many threads, how to place them, how to express communication, and how to schedule communication), so that software is hard to build and not very portable, but is usually efficient. Most recent models are near the center of this spectrum, exploring the best tradeoffs between expressiveness and performance. A few models have achieved both abstractness and efficiency. Both kinds of models raise the possibility of parallelism as part of the mainstream of computing.

/pdf/models-and-languages-for-parallel-computation-1sticvkm4u.pdf

Models and languages for parallel computation

The goal of the Pandore system is to allow the execution of parallel algorithms on DMPCs (Distributed Memory Parallel Computers) without having to take into account the low-level characteristics of the target distributed computer to program the algorithm. No explicit process definition and interprocess communications are needed. Parallelization is achieved through logical data organization. The Pandore system provides the user with a mean to specify data partitioning and data distribution over a domain of virtual processors for each parallel step of his algorithm.At compile time, Pandore splits the original program into parallel processes. Each process will execute some appropriate parts of the original code, according to the given data decomposition. In order to achieve a correct utilization of the data structures distributed over the processors, the Pandore system provides an execution scheme based on a communication layer, which is an abstraction of a message-passing architecture. This intermediate level is them implemented using the effective primitives of the real architecture (in our specific case, an Intel iPSC/2).

https://hal.inria.fr/inria-00075363/document

Pandore: a system to manage data distribution

While the proliferation of cloud services have greatly impacted our society, how green are these services is yet to be answered. Although, demand escalation for green services has grown due to societal awareness, the approaches to provide green services and establish Green SLAs remain oblivious for cloud or infrastructure providers. The main challenge for cloud provider is to manage Green SLAs with their customers while satisfying their business objectives, such as maximizing profits by lowering expenditure for green energy. Since, Green SLA needs to be proposed based on the presence of green energy, the intermittent nature of renewable sources makes it difficult to be achieved. In response, this paper presents a scheme for green energy management in the presence of explicit and implicit integration of renewable energy in data center. More specifically we propose three contributions: i) we introduce the concept of virtualization of green energy to address the uncertainty of green energy availability, ii) we extend the Cloud Service Level Agreement (CSLA) language to support Green SLA by introducing two new threshold parameters and iii) we introduce greenSLA algorithm which leverages the concept of virtualization of green energy to provide per interval specific Green SLA . Experiments were conducted with real workload profile from PlanetLab and server power model from SPECpower to demonstrate that, Green SLA can be successfully established and satisfied without incurring higher cost.

/pdf/exploiting-renewable-sources-when-green-sla-becomes-a-si726jt8op.pdf

Exploiting Renewable Sources: When Green SLA Becomes a Possible Reality in Cloud Computing

The emergence of dynamic execution environments such as Grids forces applications to take dynamicity into account. Whereas sudden resource disappearance can be handled thanks to fault-tolerance techniques, these approaches are usually not well suited when resource disappearance is announced in advance. However, this case occurs in particular for resource preemption due to resource sharing or maintenance operations. Similarly, fault-tolerance techniques commonly do not take into account resource appearance. On the other side, dynamic adaptation covers techniques for handling changes in the execution environment. This article presents a framework intended to help developers in the task of designing dynamically adaptable (but not fault-tolerant) components. This article puts the emphasis on an experimental evaluation of the cost of using such a framework.

https://hal.archives-ouvertes.fr/hal-00498836/document

A framework for dynamic adaptation of parallel components

To ease the task of programming parallel and distributed applications, the Do! project aims at the automatic generation of distributed code from multi-threaded Java programs. We provide a parallel programming model, embedded in a framework that constraints parallelism without any extension to the Java language. This framework is described here and is used as a basis to generate distributed programs.

/pdf/a-framework-for-parallel-programming-in-java-1451weibf6.pdf

A Framework for Parallel Programming in JAVA

As Grid architectures provide resources that fluctuate, applications that should be run on such environments must be able to take into account the changes that may occur. This document describes how applications can be built from components that may dynamically adapt themselves. We propose a generic framework to help the developpers of such components. In the case of a component that encapsulates a parallel code, a consistency model for the dynamic adaptation is defined. An implementation of a restricted consistency model allowed us to experiment our ideas.

/pdf/dynamic-adaptation-for-grid-computing-59izcc5mcj.pdf

Jean-Louis Pazat

Papers

Pandore: a system to manage data distribution

Exploiting Renewable Sources: When Green SLA Becomes a Possible Reality in Cloud Computing

A framework for dynamic adaptation of parallel components

A Framework for Parallel Programming in JAVA

Dynamic adaptation for grid computing