Multicore parallel programming has some very difficult problems such as deadlocks during synchronizations and race conditions brought by concurrency. Added to the difficulty is the lack of a simple, well-accepted computing model for multicore architectures--because of that it is hard to develop powerful programming environments and debugging tools. To tackle the challenges, we promote a generalized stream computing model, inspired by previous researches on stream computing, that unifies parallelization strategies for programming language design, compiler design and operating system design. Our model provides a high-level abstraction in designing language constructs to convey concepts of concurrent operations, in organizing a program's runtime layout for parallel execution, and in scheduling concurrent instruction blocks through runtime and or operating systems. In this paper, we give a high-level description of the proposed model: we define the foundation of the model, show its simplicity through algebraic computational operation analysis, illustrate a programming framework enabled by the model, and demonstrate its potential through powerful design options for programming languages, compilers and operating systems.
Jade @cite_12 represents an important experiment on parallel programming language design. Jade preserves the serial semantics of a program, implicitly exploits task parallelism, and moves data closer to processors. However, if it was designed for a smooth transition from sequential programming to parallel programming, Jade's dependence on its type system and explicit object-access control still exposes low-level synchronizations to programmers. While arguably such low-level controls provide programming flexibility, not all the details are essential to algorithm design. On the other hand, we might consider that Jade lacks the power for defining concurrent execution structures in a larger program-scope.
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2028267160 2170108472 1904065432 2130570838
Jade is a portable, implicitly parallel language designed for exploiting task-level concurrency.Jade programmers start with a program written in a standard serial, imperative language, then use Jade constructs to declare how parts of the program access data. The Jade implementation uses this data access information to automatically extract the concurrency and map the application onto the machine at hand. The resulting parallel execution preserves the semantics of the original serial program. We have implemented Jade as an extension to C, and Jade implementations exist for s hared-memory multiprocessors, homogeneous message-passing machines, and heterogeneous networks of workstations. In this atricle we discuss the design goals and decisions that determined the final form of Jade and present an overview of the Jade implementation. We also present our experience using Jade to implement several complete scientific and engineering applications. We use this experience to evaluate how the different Jade language features were used in practice and how well Jade as a whole supports the process of developing parallel applications. We find that the basic idea of preserving the serial semantics simplifies the program development process, and that the concept of using data access specifications to guide the parallelization offers significant advantages over more traditional control-based approaches. We also find that the Jade data model can interact poorly with concurrency patterns that write disjoint pieces of a single aggregate data structure, although this problem arises in only one of the applications. The authors present Jade, a high-level parallel programming language for managing course-grain concurrency. Jade simplifies programming by providing the programmer with the abstractions of sequential execution and a shared address space. Jade programmers augment sequential, imperative programs with constructs that declare how parts of the program access data; the Jade implementation dynamically interprets this information to execute the program in parallel. This parallel execution preserves the serial semantics of the original program. Jade has been implemented as an extension to C on shared-memory multiprocessors, a message-passing machine, networks of heterogeneous workstations, and systems with special-purpose functional units. Programs written in Jade run on all of these platforms without modification. > JADE (Java Agent Development Framework) is a software framework to make easy the development of multi-agent applications in compliance with the FIPA specifications. JADE can then be considered a middle-ware that implements an efficient agent platform and supports the development of multi agent systems. JADE agent platform tries to keep high the performance of a distributed agent system implemented with the Java language. In particular, its communication architecture tries to offer flexible and efficient messaging, transparently choosing the best transport available and leveraging state-of-the-art distributed object technology embedded within Java runtime environment. JADE uses an agent model and Java implementation that allow good runtime efficiency, software reuse, agent mobility and the realization of different agent architectures. Commercial applications such as databases and Web servers constitute the most important market segment for high-performance servers. Among these applications, on-line transaction processing (OLTP) workloads provide a challenging set of requirements for system designs since they often exhibit inefficient executions dominated by a large memory stall component. This behavior arises from large instruction and data footprints and high communication miss rates. A number of recent studies have characterized the behavior of commercial workloads and proposed architectural features to improve their performance. However, there has been little research on the impact of software and compiler-level optimizations for improving the behavior of such workloads. This paper provides a detailed study of profile-driven compiler optimizations to improve the code layout in commercial workloads with large instruction footprints. Our compiler algorithms are implemented in the context of Spike, an executable optimizer for the Alpha architecture. Our experiments use the Oracle commercial database engine running an OLTP workload, with results generated using both full system simulations and actual runs on Alpha multiprocessors. Our results show that code layout optimizations can provide a major improvement in the instruction cache behavior, providing a 55 to 65 reduction in the application misses for 64-128K caches. Our analysis shows that this improvement primarily arises from longer sequences of consecutively executed instructions and more reuse of cache lines before they are replaced. We also show that the majority of application instruction misses are caused by self-interference. However, code layout optimizations significantly reduce the amount of self-interference, thus elevating the relative importance of interference with operating system code. Finally, we show that better code layout can also provide substantial improvements in the behavior of other memory system components such as the instruction TLB and the unified second-level cache. The overall performance impact of our code layout optimizations is an improvement of 1.33 times in the execution time of our workload.