虚拟化现有的流体程序

IF 2.1 4区 计算机科学 Q3 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE ACM Journal on Emerging Technologies in Computing Systems Pub Date : 2022-08-30 DOI:10.1145/3558550
Caleb Winston, Max Willsey, L. Ceze
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引用次数: 0

摘要

流体自动化,即通过编程操作小流体来执行实验室协议的做法,极大地提高了生物学家和化学家的生产力。大多数流体程序(通常称为协议)都是使用API编写的,这些API通过参考设备上的物理位置将协议耦合到特定硬件。这种耦合使得隔离变得不可能,从而阻止了协议在同一设备上的可移植性、并发执行和组合。我们提出了一种用于在单个运行时系统之上虚拟化现有流体协议而不进行修改的系统。我们的系统为每个运行的协议提供了设备的独立视图,允许它假设自己只能访问硬件。我们提供了一个概念验证实现,可以同时执行和编写使用流行的Opentrons Python API编写的协议。与串行执行相比,并发执行实现了近乎线性的加速,因为协议花费了大量时间等待。
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Virtualizing Existing Fluidic Programs
Fluidic automation, the practice of programmatically manipulating small fluids to execute laboratory protocols, has led to vastly increased productivity for biologists and chemists. Most fluidic programs, commonly referred to as protocols, are written using APIs that couple the protocol to specific hardware by referring to the physical locations on the device. This coupling makes isolation impossible, preventing portability, concurrent execution, and composition of protocols on the same device. We propose a system for virtualizing existing fluidic protocols on top of a single runtime system without modification. Our system presents an isolated view of the device to each running protocol, allowing it to assume it has sole access to hardware. We provide a proof-of-concept implementation that can concurrently execute and compose protocols written using the popular Opentrons Python API. Concurrent execution achieves near-linear speedup over serial execution, since protocols spend much of their time waiting.
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来源期刊
ACM Journal on Emerging Technologies in Computing Systems
ACM Journal on Emerging Technologies in Computing Systems 工程技术-工程:电子与电气
CiteScore
4.80
自引率
4.50%
发文量
86
审稿时长
3 months
期刊介绍: The Journal of Emerging Technologies in Computing Systems invites submissions of original technical papers describing research and development in emerging technologies in computing systems. Major economic and technical challenges are expected to impede the continued scaling of semiconductor devices. This has resulted in the search for alternate mechanical, biological/biochemical, nanoscale electronic, asynchronous and quantum computing and sensor technologies. As the underlying nanotechnologies continue to evolve in the labs of chemists, physicists, and biologists, it has become imperative for computer scientists and engineers to translate the potential of the basic building blocks (analogous to the transistor) emerging from these labs into information systems. Their design will face multiple challenges ranging from the inherent (un)reliability due to the self-assembly nature of the fabrication processes for nanotechnologies, from the complexity due to the sheer volume of nanodevices that will have to be integrated for complex functionality, and from the need to integrate these new nanotechnologies with silicon devices in the same system. The journal provides comprehensive coverage of innovative work in the specification, design analysis, simulation, verification, testing, and evaluation of computing systems constructed out of emerging technologies and advanced semiconductors
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