Dataflow/Actor-Oriented language for the design of complex signal processing systems

International audienceSignal processing algorithms become more and more complex and the algorithm architecture adaptation and design processes cannot any longer rely only on the intuition of the designers to build efficient systems. Specific tools and methods are needed to cope with the increasing complexity of both algorithms and platforms. This paper presents a new framework which allows the specification, design, simulation and implementation of a system operating at a higher level of abstraction compared to current approaches. The framework is base on the usage of a new actor/dataflow oriented language called CAL. Such language has been specifically designed for modelling complex signal processing systems. CAL data flow models expose the intrinsic concurrency of the algorithms by employing the notions of actor programming and dataflow. Concurrency and parallelism are very important aspects of embedded system design as we enter in the multicore era. The design framework is composed by a simulation platform and by Cal2C and CAL2HDL code generators. This paper described in details the principles on which such code generators are based and shows how efficient software (C) and hardware (VHDL and Verilog) code can be generated by appropriate CAL models. Results on a real design case, a MPEG-4 Simple Profile decoder, show that systems obtained with the hardware code generator outperform the hand written VHDL version both in terms of performance and resource usage. Concerning the C code generator results, the results show that the synthesized C-software mapped on a SystemC scheduler platform, is much faster than the simulated CAL dataflow program and approaches handwritten C versions

Virtual Machine Support for Many-Core Architectures: Decoupling Abstract from Concrete Concurrency Models

The upcoming many-core architectures require software developers to exploit concurrency to utilize available computational power. Today's high-level language virtual machines (VMs), which are a cornerstone of software development, do not provide sufficient abstraction for concurrency concepts. We analyze concrete and abstract concurrency models and identify the challenges they impose for VMs. To provide sufficient concurrency support in VMs, we propose to integrate concurrency operations into VM instruction sets. Since there will always be VMs optimized for special purposes, our goal is to develop a methodology to design instruction sets with concurrency support. Therefore, we also propose a list of trade-offs that have to be investigated to advise the design of such instruction sets. As a first experiment, we implemented one instruction set extension for shared memory and one for non-shared memory concurrency. From our experimental results, we derived a list of requirements for a full-grown experimental environment for further research

Schema architecture and their relationships to transaction processing in distributed database systems

We discuss the different types of schema architectures which could be supported by distributed database systems, making a clear distinction between logical, physical, and federated distribution. We elaborate on the additional mapping information required in architecture based on logical distribution in order to support retrieval as well as update operations. We illustrate the problems in schema integration and data integration in multidatabase systems and discuss their impact on query processing. Finally, we discuss different issues relevant to the cooperation (or noncooperation) of local database systems in a heterogeneous multidatabase system and their relationship to the schema architecture and transaction processing

Design and Implementation of a Distributed Middleware for Parallel Execution of Legacy Enterprise Applications

A typical enterprise uses a local area network of computers to perform its business. During the off-working hours, the computational capacities of these networked computers are underused or unused. In order to utilize this computational capacity an application has to be recoded to exploit concurrency inherent in a computation which is clearly not possible for legacy applications without any source code. This thesis presents the design an implementation of a distributed middleware which can automatically execute a legacy application on multiple networked computers by parallelizing it. This middleware runs multiple copies of the binary executable code in parallel on different hosts in the network. It wraps up the binary executable code of the legacy application in order to capture the kernel level data access system calls and perform them distributively over multiple computers in a safe and conflict free manner. The middleware also incorporates a dynamic scheduling technique to execute the target application in minimum time by scavenging the available CPU cycles of the hosts in the network. This dynamic scheduling also supports the CPU availability of the hosts to change over time and properly reschedule the replicas performing the computation to minimize the execution time. A prototype implementation of this middleware has been developed as a proof of concept of the design. This implementation has been evaluated with a few typical case studies and the test results confirm that the middleware works as expected