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Using Mpi Portable Parallel Programming With The Message Passing Interface

This review covers research on the topic of mixed criticality systems that has been published since Vestal’s 2007 paper. It covers the period up to and including December 2015. The review is organised into the following topics: introduction and motivation, models, single processor analysis (including job-based, hard and soft tasks, fixed priority and EDF scheduling, shared resources and static and synchronous scheduling), multiprocessor analysis, related topics, realistic models, formal treatments, and systems issues. An appendix lists funded projects in the area of mixed criticality.

/pdf/mixed-criticality-systems-a-review-3ftn7gd29e.pdf

Mixed Criticality Systems - A Review

Four relations are defined the use of which allow a reliability network to be expressed as a mathematical statement. Series and active and standby redundancy connections are allowed. The possibility of requiring more than one of the active branches to be operative is included. At the very least the result allows for typing in place of drawing a network description.

http://ieeexplore.ieee.org/iel5/24/5216426/05216446.pdf

Network Calculus

The Kalray MPPA-256 processor integrates 256 user cores and 32 system cores on a chip with 28nm CMOS technology. Each core implements a 32-bit 5-issue VLIW architecture. These cores are distributed across 16 compute clusters of 16+1 cores, and 4 quad-core I/O subsystems. Each compute cluster and I/O subsystem owns a private address space, while communication and synchronization between them is ensured by data and control Networks-On-Chip (NoC). The MPPA-256 processor is also fitted with a variety of I/O controllers, in particular DDR, PCI, Ethernet, Interlaken and GPIO. We demonstrate that the MPPA-256 processor clustered manycore architecture is effective on two different classes of applications: embedded computing, with the implementation of a professional H.264 video encoder that runs in real-time at low power; and high-performance computing, with the acceleration of a financial option pricing application. In the first case, a cyclostatic dataflow programming environment is utilized, that automates application distribution over the execution resources. In the second case, an explicit parallel programming model based on POSIX processes, threads, and NoC-specific IPC is used.

/pdf/a-clustered-manycore-processor-architecture-for-embedded-and-1tzm8lc214.pdf

A clustered manycore processor architecture for embedded and accelerated applications

This survey covers research into mixed criticality systems that has been published since Vestal’s seminal paper in 2007, up until the end of 2016. The survey is organised along the lines of the major research areas within this topic. These include single processor analysis (including fixed priority and Earliest Deadline First (EDF) scheduling, shared resources, and static and synchronous scheduling), multiprocessor analysis, realistic models, and systems issues. The survey also explores the relationship between research into mixed criticality systems and other topics such as hard and soft time constraints, fault tolerant scheduling, hierarchical scheduling, cyber physical systems, probabilistic real-time systems, and industrial safety standards.

/pdf/a-survey-of-research-into-mixed-criticality-systems-38qb9k0dr3.pdf

A Survey of Research into Mixed Criticality Systems

The requirement of high performance computing at low power can be met by the parallel execution of an application on a possibly large number of programmable cores. However, the lack of accurate timing properties may prevent parallel execution from being applicable to time-critical applications. We illustrate how this problem has been addressed by suitably designing the architecture, implementation, and programming model, of the Kalray MPPA®-256 single-chip many-core processor. The MPPA® -256 (Multi-Purpose Processing Array) processor integrates 256 processing engine (PE) cores and 32 resource management (RM) cores on a single 28nm CMOS chip. These VLIW cores are distributed across 16 compute clusters and 4 I/O subsystems, each with a locally shared memory. On-chip communication and synchronization are supported by an explicitly addressed dual network-on-chip (NoC), with one node per compute cluster and 4 nodes per I/O subsystem. Off-chip interfaces include DDR, PCI and Ethernet, and a direct access to the NoC for low-latency processing of data streams. The key architectural features that support time-critical applications are timing compositional cores, independent memory banks inside the compute clusters, and the data NoC whose guaranteed services are determined by network calculus. The programming model provides communicators that effectively support distributed computing primitives such as remote writes, barrier synchronizations, active messages, and communication by sampling. POSIX time functions expose synchronous clocks inside compute clusters and mesosynchronous clocks across the MPPA®-256 processor.

Time-critical computing on a single-chip massively parallel processor

The Kalray MPPA®-256 is a single-chip manycore processor that integrates 256 user cores and 32 system cores in 28 nm CMOS technology. These cores are distributed across 16 compute clusters of 16+1 cores, and 4 quad-core I/O subsystems. Each compute cluster and I/O subsystem owns a private address space, while communication and synchronization between them is ensured by data and control Networks-on-Chip (NoC). This processor targets embedded applications whose program- ming models fall within the following classes: Kahn Process Networks (KPN), as motivated by media processing; single program multiple data (SPMD), traditionally used for numerical kernels; and time-triggered control systems. We describe a run-time environment that supports these classes of programming models and their composition. This environment combines classic POSIX single-process multi-threaded execution inside the compute clusters and I/O subsystems, with a set of specific Inter-Process Communication (IPC) primitives that exploit the NoC architecture. We combine these primitives in order to provide the run-time support for the different target programming models. Interestingly enough, all these NoC-specific IPC primitives can be mapped to a subset of the classic synchronous and asynchronous POSIX file descriptor operations. This design thus extends the canonical ‘pipe-and-filters’ software component model, where POSIX processes are the atomic components, and IPC instances are the connectors.

A Distributed Run-Time Environment for the Kalray MPPA®-256 Integrated Manycore Processor☆

In real-time and safety-critical systems, the move towards mul-ticores is becoming unavoidable in order to keep pace with the increasing required processing power and to meet the high integration trend while maintaining a reasonable power consumption. However, standard multicore systems are mainly designed to increase average performance, whereas embedded systems have additional requirements with respect to safety, reliability and realtime behavior. Therefore, the shift to multicores raises several challenges the embedded community has to face. These challenges involve the design of certifiable multicore platforms, the management of shared resources and the development/integration of parallel software. These issues are encountered at different steps of system development, from modeling and design to software implementation and hardware deployment. Therefore, both multi-core/semiconductor manufacturers and the real-time community have to bridge the gap in order to meet the challenges imposed by multicores. The goal of this paper is to trigger such a discussion as an attempt to bridge the gap between the two worlds and to raise awareness about the hurdles and challenges that need to be tackled.

The shift to multicores in real-time and safety-critical systems

The embedded system industry is facing an increasing pressure for migrating from single-core to multi- and many-core platforms for size, performance and cost purposes. Real-time embedded system design follows this trend by integrating multiple applications with different safety criticality levels into a common platform. Scheduling mixed-criticality applications on today's multi/many-core platforms and providing safe worst-case response time bounds for the real-time applications is challenging given the shared platform resources. For instance, sharing of memory buses introduces delays due to contention, which are non-negligible. Bounding these delays is not trivial, as one needs to model all possible interference scenarios. In this work, we introduce a combined analysis of computing, memory and communication scheduling in a mixed-criticality setting. In particular, we propose: (1) a mixed-criticality scheduling policy for cluster-based many-core systems with two shared resource classes, i.e., a shared multi-bank memory within each cluster, and a network-on-chip for inter-cluster communication and access to external memories; (2) a response time analysis for the proposed scheduling policy, which takes into account the interferences from the two classes of shared resources; and (3) a design exploration framework and algorithms for optimizing the resource utilizations under mixed-criticality timing constraints. The considered cluster-based architecture model describes closely state-of-the-art many-core platforms, such as the Kalray MPPA®-256. The applicability of the approach is demonstrated with a real-world avionics application. Also, the scheduling policy is compared against state-of-the-art scheduling policies based on extensive simulations with synthetic task sets.

Benoît Dupont de Dinechin

Papers

A clustered manycore processor architecture for embedded and accelerated applications

Time-critical computing on a single-chip massively parallel processor

A Distributed Run-Time Environment for the Kalray MPPA®-256 Integrated Manycore Processor☆

The shift to multicores in real-time and safety-critical systems

Mixed-criticality scheduling on cluster-based manycores with shared communication and storage resources