面向多任务流应用的RCS计算资源虚拟化

L. Kirischian, V. Dumitriu, P. Chun
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引用次数: 1

摘要

FPGA资源在多模态和多任务工作负载的时域分布的可能性在概念上允许逻辑、通信和输入/输出资源的虚拟化,类似于高级传统计算机(例如超标量)的内存虚拟化。反过来,这可以显著提高基于FPGA的可重构计算系统(RCS)的成本效益。在提出的“概念验证”研究中,已经调查,开发和测试了以下主题:i)支持应用特定虚拟处理器(ASVP)动态分配的平台架构,ii)从虚拟硬件组件(VHC)中运行时ASVP的片上组装机制,以及iii)在FPGA设备的预定区域中运行时片上组件(VHC)重新定位机制。上述机制已经在一个专门开发的平台上实现和测试:多任务自适应可重构系统(MARS)平台。MARS的实际应用是为下一代星载计算平台制作高性能多模式立体视觉系统(200帧/秒)原型。
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Virtualization of Computing Resources in RCS for Multi-task Stream Applications
The possibility for distribution of FPGA resources in the temporal domain for multi-modal & multi-task workloads conceptually allows virtualization of logic, communication and input/output resources similar to memory virtualization in advanced conventional computers (e.g. superscalar). This, in turn, can dramatically increase the cost-effectiveness of FPGA based Reconfigurable Computing Systems (RCS). In the presented “proof-of-concept” research the following topics have been investigated, developed and tested: i) architecture of a platform to support the dynamic allocation of Application Specific Virtual Processors (ASVP), ii) mechanisms for run-time on-chip assembly of ASVP from Virtual Hardware Components (VHC) and iii) mechanisms for run-time on-chip components (VHC) relocation in predetermined regions of the FPGA device. The above mechanisms have been implemented and tested on a specially developed platform: the Multi-task Adaptive Reconfigurable System (MARS) Platform. The actual application of MARS was prototyping a high-performance multi-mode stereo-vision system (200 fps) for the next generation of space-borne computing platforms.
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