Multiprocessing architectures provide hardware for executing multiple tasks simultaneously via techniques such as simultaneous multithreading and symmetric multiprocessing. The problem addressed by this paper is that even when tasks that are executing concurrently do not communicate, they may interfere by affecting each other's timing. For cyberphysical system applications, such interference can nullify many of the advantages offered by parallel hardware. In this paper, we argue for temporal semantics in layers of abstraction in computing. This will enable us to achieve temporal isolation on multiprocessing architectures. We discuss techniques at the microarchitecture level, in the memory hierarchy, in on-chip communication, and in the instruction-set architecture that can provide temporal semantics and control over timing.
This paper presents the concept of adaptive programs, whose computation and communication structures can morph to adapt to environmental and demand changes to save energy and computing resources. In this approach, programmers write one single program using a language at a higher level of abstraction. The compiler will exploit the properties of the abstractions to generate an adaptive program that is able to adjust computation and communication structures to environmental and demand changes.We develop a technique, called StreaMorph, that exploits the properties of stream programs' Synchronous Dataflow (SDF) programming model to enable runtime stream graph transformation. The StreaMorph technique can be used to optimize memory usage and to adjust core utilization leading to energy reduction by turning off idle cores or reducing operating frequencies. The main challenge for such a runtime transformation is to maintain consistent program states by copying states between different stream graph structures, because a stream program optimized for different numbers of cores often has different sets of filters and inter-filter channels. We propose an analysis that helps simplify program state copying processes by minimizing copying of states based on the properties of the SDF model.Finally, we implement the StreaMorph method in the StreamIt compiler. Our experiments on the Intel Xeon E5450 show that using StreaMorph to minimize the number of cores used from eight cores to one core, e.g. when streaming rates become lower, can reduce energy consumption by 76.33% on average. Using StreaMorph to spread workload from four cores to six or seven cores, e.g. when more cores become available, to reduce operating frequencies, can lead to 10% energy reduction. In addition, StreaMorph can lead to a buffer size reduction of 82.58% in comparison with a straightforward inter-core filter migration technique when switching from using eight cores to one core.
Abstract-Deploying real-time control systems software on multiprocessors requires distributing tasks on multiple processing nodes and coordinating their executions using a protocol. One such protocol is the discrete-event (DE) model of computation. In this paper, we investigate distributed discrete-event (DE) with null-message protocol (NMP) on a multicore system for real-time control software. We illustrate analytically and experimentally that even with the null-message deadlock avoidance scheme in the protocol, the system can deadlock due to inter-core message dependencies. We identify two central reasons for such deadlocks: 1) the lack of an upper-bound on packet transmission rates and processing capability, and 2) an unknown upper-bound on the communication network delay. To address these, we propose using architectural features such as timing control and real-time network-on-chips to prevent such message-dependent deadlocks. We employ these architectural techniques in conjunction with a distributed DE strategy called PTIDES for an illustrative car wash station example and later follow it with a more realistic tunnelling ball device application.
Hierarchical SDF models are not compositional: a composite SDF actor cannot be represented as an atomic SDF actor without loss of information that can lead to rate inconsistency or deadlock. Motivated by the need for incremental and modular code generation from hierarchical SDF models, we introduce in this paper DSSF profiles. DSSF (Deterministic SDF with Shared FIFOs) forms a compositional abstraction of composite actors that can be used for modular compilation. We provide algorithms for automatic synthesis of non-monolithic DSSF profiles of composite actors given DSSF profiles of their sub-actors. We show how different trade-offs can be explored when synthesizing such profiles, in terms of compactness (keeping the size of the generated DSSF profile small) versus reusability (maintaining necessary information to preserve rate consistency and deadlock-absence) as well as algorithmic complexity. We show that our method guarantees maximal reusability and report on a prototype implementation.
Abstract-One issue with today's Internet is that it only supports besteffort service; hence Internet users often experience unpredicted delay. Deployment of new real-time, highly reliable applications that require fixed delay bound on packets, such as remote surgery, become very difficult. Communication environment that can assert a strict delay bound will help estimate the worst-case execution time of distributed real-time applications.This paper revises a flaw in estimation of delay bound and an incorrect proof for of a non-preemptive Earliest Deadline First (EDF) packet scheduling algorithm used in packet scheduling for implementing real-time communication services in packet-switching network described in [1,2,3], which is one of few seminal works on guaranteed service in packet-switching network. We discuss the found flaw then correct the error and provide a substitute proof for this new correction.
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