Science Dynamic Model in TVM AWS AI© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Models with dynamism ● Control flow (if, loop, etc) ● Dynamic shapes ○ Dynamic inputs: Limitation of TVM/graph runtime ● Cannot compile and run dynamic models© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Support dynamic model in TVM ● Support Any-dim in typing ● Use Use shape function to compute the type at runtime ● Virtual machine as a new runtime for Relay ● Dynamic codegen (WIP) ○ Kernel dispatch for a single op ○ Graph dispatch for a (sub-)graph In collaboration

application generally consists of one or more RequestHandler subclasses, an Application object which routes incoming requests to handlers, and a main() function to start the server. A minimal “hello world” 6.2.3 tornado.routing — Basic routing implementation Flexible routing implementation. Tornado routes HTTP requests to appropriate handlers using Router class implementations. The tornado.web. Application server = HTTPServer(router) ReversibleRouter interface adds the ability to distinguish between the routes and reverse them to the original urls using route’s name and additional arguments. Application is

application generally consists of one or more RequestHandler subclasses, an Application object which routes incoming requests to handlers, and a main() function to start the server. A minimal “hello world” version 4.3.tornado.routing — Basic routing implementation Flexible routing implementation. Tornado routes HTTP requests to appropriate handlers using Router class implementations. The tornado.web.Application server = HTTPServer(router) ReversibleRouter interface adds the ability to distinguish between the routes and reverse them to the original urls using route’s name and additional arguments. Application is

releases. Acquisition executives must also streamline the decision process by empowering small, dynamic, government-contractor teams. Agile cannot solve all of the DoD’s IT acquisition challenges, but engineering processes, managing requirements, and developing cost estimates for programs with a dynamic scope. Experience indicates that cultural changes must occur if programs are to implement Agile throughout development to ensure high operational value Agile is built around a culture of small, dynamic, empowered teams actively collaborating with stakeholders throughout product development. Agile

Infrastructure Improvements to TVM o_uTVM: support for microcontrollers in TVM o_ Virtual Machine and dynamic NNs support (w/ AWS folks) o_ Improved NLP support, with focus on transformers QQ octoML Core Infrastructure towards production quality. o _VM compiler VM runtime VM serialization Dynamic Shape Support Dynamic Shape Allocation o Dynamic Shape Code generation ee Looking for more contributions in this part of ncubator-tvm/pull/3560 了 e， Enables future optimizations fn emain() -，Tensor[tk,)，f32] { and end-to-end dynamic Tet tl 引 -。 Let t2 3 memory planning,， storage

1368 74 Interactive Utilities 1369 75 Lazy Artifacts 1379 76 LibCURL 1380 77 LibGit2 1381 78 Dynamic Linker 1429 79 Linear Algebra 1433 79.1 Special matrices . . . . . . . . . . . . . . . . . . . performance, yet domain experts have largely moved to slower dynamic languages for daily work. We believe there are many good reasons to prefer dynamic languages for these applications, and we do not expect performance-intensive applications. The Julia programming language fills this role: it is a flexible dynamic 2CHAPTER 1. JULIA 1.11 DOCUMENTATION 3 language, appropriate for scientific and numerical computing

1368 74 Interactive Utilities 1369 75 Lazy Artifacts 1379 76 LibCURL 1380 77 LibGit2 1381 78 Dynamic Linker 1429 79 Linear Algebra 1433 79.1 Special matrices . . . . . . . . . . . . . . . . . . . performance, yet domain experts have largely moved to slower dynamic languages for daily work. We believe there are many good reasons to prefer dynamic languages for these applications, and we do not expect performance-intensive applications. The Julia programming language fills this role: it is a flexible dynamic 2CHAPTER 1. JULIA 1.11 DOCUMENTATION 3 language, appropriate for scientific and numerical computing

1368 74 Interactive Utilities 1369 75 Lazy Artifacts 1379 76 LibCURL 1380 77 LibGit2 1381 78 Dynamic Linker 1429 79 Linear Algebra 1433 79.1 Special matrices . . . . . . . . . . . . . . . . . . . performance, yet domain experts have largely moved to slower dynamic languages for daily work. We believe there are many good reasons to prefer dynamic languages for these applications, and we do not expect performance-intensive applications. The Julia programming language fills this role: it is a flexible dynamic 2CHAPTER 1. JULIA 1.11 DOCUMENTATION 3 language, appropriate for scientific and numerical computing

. . . . . . . . . . . . . . 1437 77 Lazy Artifacts 1440 78 LibCURL 1441 79 LibGit2 1442 80 Dynamic Linker 1490 81 Linear Algebra 1494 81.1 Special matrices . . . . . . . . . . . . . . . . . . . experts have largely moved to slower dynamic languages for daily work. We believe there are many good reasons to prefer 2CHAPTER 1. JULIA 1.13-DEV DOCUMENTATION 3 dynamic languages for these applications performance-intensive applications. The Julia programming language fills this role: it is a flexible dynamic language, appropriate for scientific and numerical computing, with performance comparable to traditional

. . . . . . . . . . . . . . 1435 77 Lazy Artifacts 1438 78 LibCURL 1439 79 LibGit2 1440 80 Dynamic Linker 1488 81 Linear Algebra 1492 81.1 Special matrices . . . . . . . . . . . . . . . . . . . experts have largely moved to slower dynamic languages for daily work. We believe there are many good reasons to prefer 2CHAPTER 1. JULIA 1.12-RC1 DOCUMENTATION 3 dynamic languages for these applications performance-intensive applications. The Julia programming language fills this role: it is a flexible dynamic language, appropriate for scientific and numerical computing, with performance comparable to traditional