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首页> 外文期刊>Procedia Computer Science >Architecture, Languages, Compilation and Hardware support for Emerging ManYcore systems (ALCHEMY): Preface
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Architecture, Languages, Compilation and Hardware support for Emerging ManYcore systems (ALCHEMY): Preface

机译：新兴ManYcore系统的体系结构，语言，编译和硬件支持（ALCHEMY）：前言

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Manycore systems are one of the key enabler technologies for most of current computational paradigms, including Internet of things, data-centers on chip and big data processing. These paradigms are characterized by tight and demanding requirements such as code portability, dynamicity, high performance, usability, predictability, reliability, low power and security. This combination of requirements has led to heterogeneous manycore systems which are extremely challenging to design and to program. As a result, a large body of research has focused on development of languages, simulation environments and analysis tools that allow to model and predict the behavior of this type of systems from early design stages. ALCHEMY 2017 presents five research works addressing the challenges of code portability, high performance, usability, security and reliability in manycore systems. These are namely: 1. ” An OpenMP backend for the Sigma-C streaming language , addresses the software portability challenge of manycore architectures. It proposes an implementation of an OpenMP backend for the SigmaC language, a cycle-static data flow abstraction to program many-core embedded platforms. Its compilation scheme allows for utilization of future manycore embedded systems such as Kalray’s MPPA. 2. A multi-level optimization strategy to improve the performance of the stencil computation combines manual vectorization, space tiling and stencil composition for achieving high performance of stencil kernels on manycore systems. The evaluation with three compilers (Intel, Clang and GCC) and two target multi-core platforms (Intel Broadwell and Ivybridge) reports better results compared to the state of the art. 3. A Distributed Shared Memory Model and C++ Templated Meta-Programming Interface for the Epiphany RISC Array Processor addresses the usability challenge. It proposes techniques for data layout and parallel loop order abstraction as a parallel programming API targeting the Epiphany architecture. This results into a transparent distributed shared memory (DSM) model for Epiphany that eliminates the need to manage local data movement between cores. 4. Towards Protected MPSoC Communication for Information Protection against a Malicious NoC deals with vulnerabilities on Network-on-Chip (NoC). The authors propose a security protocol which allows the secure communication among the cores of the system, even in the presence of Trojan insertions at the NoC whose aim is to modify and steal data. 5. GPU-Accelerated Real-Time Path Planning and the Predictable Execution Model addresses the reliability challenge and tackles the important problem of ensuring reliable Worst Case Execution Time for Real-Time and Cyber Physical Systems. While considering heterogeneous (CPU/GPU), the idea is to separate memory and processor operations through Time-Division Multiplexing (TDM).
机译：Manycore系统是大多数当前计算范例的关键促成技术之一，包括物联网，片上数据中心和大数据处理。这些范式的特点是要求严格，例如代码可移植性，动态性，高性能，可用性，可预测性，可靠性，低功耗和安全性。需求的组合导致了异构多核系统，这对设计和编程都极具挑战性。结果，大量的研究集中在语言，仿真环境和分析工具的开发上，这些工具允许从早期设计阶段就对这种类型的系统的行为进行建模和预测。 ALCHEMY 2017提出了五项研究工作，以应对许多核心系统中的代码可移植性，高性能，可用性，安全性和可靠性方面的挑战。它们是：1.用于Sigma-C流语言的OpenMP后端，解决了许多核心体系结构的软件可移植性挑战。它提出了一种针对SigmaC语言的OpenMP后端的实现，这是一种对多核嵌入式平台进行编程的循环静态数据流抽象。它的编译方案允许利用未来的许多核心嵌入式系统，例如Kalray的MPPA。 2.改善模板计算性能的多级优化策略结合了手动矢量化，空间平铺和模板组合，以在许多核心系统上实现高性能的模板内核。与最新技术相比，使用三个编译器（Intel，Clang和GCC）和两个目标多核平台（Intel Broadwell和Ivybridge）进行的评估报告了更好的结果。 3.主显RISC阵列处理器的分布式共享内存模型和C ++模板元编程接口解决了可用性挑战。它提出了用于数据布局和并行循环顺序抽象的技术，作为针对Epiphany体系结构的并行编程API。这样就形成了Epiphany的透明分布式共享内存（DSM）模型，从而无需管理内核之间的本地数据移动。 4.迈向受保护的MPSoC通信以防止恶意NoC的信息，可以处理片上网络（NoC）上的漏洞。作者提出了一种安全协议，即使在NoC出现Trojan插入（旨在修改和窃取数据）的情况下，该协议也允许在系统核心之间进行安全通信。 5. GPU加速的实时路径规划和可预测的执行模型解决了可靠性挑战，并解决了确保实时和网络物理系统的最坏情况执行时间可靠的重要问题。在考虑异构（CPU / GPU）时，其想法是通过时分复用（TDM）分离内存和处理器操作。

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