【GiantPandaCV导语】本文作为从零开始学深度学习编译器的番外篇,介绍了一下深度学习框架的Data Flow和Control Flow,并基于TensorFlow解释了TensorFlow是如何在静态图中实现Control Flow的。而对于动态图来说,…
Big Data problems and applications that are suitable for implementation on DataFlow computers should not be measured using the same measures as ControlFlow computers. We propose a new methodology for benchmarking, which takes into account not only the execution time, but also the power and space,...
深度学习编译器Data Flow和Control Flow 本文介绍了一下深度学习框架的Data Flow和Control Flow,基于TensorFlow解释了TensorFlow是如何在静态图中实现Control Flow的。支持在Python层直接写Control Flow的动态图,最后基于Pytorch介绍了如何将Python层的Control Flow导出到TorchScript模型以及ONNX模型。 1. 前言 1.1. DataFlow...
【GiantPandaCV导语】本文作为从零开始学深度学习编译器的番外篇,介绍了一下深度学习框架的Data Flow和Control Flow,并基于TensorFlow解释了TensorFlow是如何在静态图中实现Control Flow的。而对于动态图来说,是支持在Python层直接写Control Flow的,最后基于Pytorch介绍了如何将Python层的Control Flow导出到TorchScript模型以...
编译原理中的数据流（data-flow）分析与控制流（control-flow）分析有何区别？数据流指的是程序每个“点...
数据流分析则是在控制流图之上进行，旨在通过迭代过程揭示出程序执行中涉及到的特定数据的流动情况。这些分析结果可用于多种目的，例如确定变量的生存周期、识别变量的定义和使用、检测死代码以及优化代码等。在控制流分析中，主要关注的是程序的控制结构，比如条件分支、循环、跳转等，通过这些结构来构建控制...
always be maintained as explicit data instead, but then the explicit data form is essentially simulating the control flow. Most of the time, using the control flow features built into a programming language is easier to understand, reason about, and maintain than simulating them in data ...
In the Control Flow, the task is the smallest unit of work, and a task requires completion (success, failure, or just completion) before subsequent tasks are handled. Workflow orchestration Process-oriented Serial or parallel tasks execution ...
I'm trying to get a better understanding of when I would need to (or should) implement logic in control flow vs using the data flow to do it all. What prompted me to start looking into control flow and it's purpose is that I'd like to refactor SSIS data flows as well as break ...
What is control flowControl flow is an orchestration of pipeline activities that includes chaining activities in a sequence, branching, defining parameters at the pipeline level, and passing arguments while invoking the pipeline on demand or from a trigger....