## CS 591 K1: Data Stream Processing and Analytics Spring 2020 ## 4 /09: Flow control and load shedding Vasiliki (Vasia) Kalavri vkalavri@bu.edu ## Keeping up with the producers • Producers can generate queue: what if the queue grows larger than available memory? • block the producer (back-pressure, flow control) ## Load management approaches ![Image](/uploads/documents/1/8/5/2/1852496083fa00bab53cdd69c80bfbf6/p7_1 applications with strict latency constraints that can tolerate approximate results. Slow down the flow of data: - The system buffers excess data for later processing, once input rates stabilize. •

### Asynchronous programming in .NET by Gerardo Lijs Twitter @GerardoLijs April 2019 ## Content What is Asynchronous Programming CPU-bound vs IO-bound Obsolete patterns Tasks and async/await Practical Count(n => Enumerable.Range(2, (int)Math.Sqrt(n) - 1).All(i => n % i > 0)); } ## Asynchronous method Task GetPrimesCountAsync(int start, int count) { return Task.Run(() => of the time you will need asynchronous to deal with IO-bound operations and the times you will use CPU-bound operations you will probably use a library that provides asynchronous methods for you to interact

## CurveBS I/O processing flow Before introducing IO processing flow, we first describe the overall architecture, data organization and topology structure of CURVE.  and non-lazy (allocated space on interface, such as read/write/aioread/aiowrite in data plane and open/create/rename/extend, etc in control plane. 2. Depending on libCurve, the application must be restarted every time the library is updated

# Optimization for number of goroutines using feedback control Yusuke MIYAKE / Pepabo R&D Institute, GMO Pepabo, Inc. 2019.07.25 GopherCon 2019 ![Image](/uploads/documents/4/2/d/f/42dfd7f07b1ef4 ## I ssues to solve for the realization 1. Selection of performance metrics 2. Finding how to control rapidly and continuously ## Performance metrics ## Performance metrics • Independent resource type based on the metrics • Continuously • Rapidly • Accurately • Feedback control meets these conditions. ## Feedback control • Tracking a given set-point using errors from the set-point. • Applying

## +23 ## Taro: Task graph-based Asynchronous Programming Using C++ Coroutine DIAN-LUN LIN 20 23 October 01 - 06 ## Agenda • Understand the motivation behind Taro • Learn to use the Taro C++ programming Conclusion ## Synchronous/Asynchronous Mechanisms Synchronous Boil the water  Multitasking! Asynchronous Wait ![Image]( motivation behind Taro • We have presented the Taro C++ programming model - Synchronous and Asynchronous mechanisms • We have presented the Taro coroutine-aware scheduling algorithm • We have presented

+24 ## Deciphering C++ Coroutines Mastering Asynchronous Control Flow ## ANDREAS WEIS ## Deciphering Coroutines - Part 2 Mastering Asynchronous Control Flow Andreas Weis CppCon 2024 ## About me - Andreas synchronization needed. ■ Green Threads cooperatively decide when to suspend and resume Intuition about control-flow is still very similar to threads ☐ Stackless We can only suspend one function at a time If we std::vector<> my_children ## Conclusion Coroutines allow for extremely powerful manipulation of control flow between functions ☑ To achieve best results, there should be some amount of uniformity between

77 8.18 Dot Syntax for Vectorizing Functions ..... 78 8.19 Further Reading ..... 80 9 Control Flow ..... 81 9.1 Compound Expressions ..... 81 9.2 Conditional Evaluation ..... 82 9.3 Short-Circuit 263 20.2 Equality and Comparison Operators ..... 264 20.3 Logical operators ..... 265 20.4 Control Flow and Short-Circuiting Operators ..... 266 20.5 Arrays With Missing Values ..... 267 20.6 Skipping 21.6 Resolving IP Addresses ..... 276 21.7 Asynchronous I/O ..... 276 21.8 Multicast ..... 277 22 Parallel Computing ..... 279 23 Asynchronous Programming ..... 280 23.1 Basic Task operations

and piping 74 8.16 Dot Syntax for Vectorizing Functions 75 8.17 Further Reading 77 9 Control Flow 79 9.1 Compound Expressions 79 9.2 Conditional Evaluation 80 9.3 Short-Circuit Evaluation 239 20.2 Equality and Comparison Operators ..... 239 20.3 Logical operators ..... 240 20.4 Control Flow and Short-Circuiting Operators ..... 242 20.5 Arrays With Missing Values ..... 243 20.6 Skipping example ..... 250 21.6 Resolving IP Addresses ..... 252 22 Parallel Computing ..... 253 23 Asynchronous Programming ..... 255 23.1 Basic Task operations ..... 255 23.2 Communicating with Channels

16.16 Dot Syntax for Vectorizing Functions ..... 94 16.17 Further Reading ..... 96 17 Control Flow ..... 97 17.1 Compound Expressions ..... 97 17.2 Conditional Evaluation ..... 98 17.3 Short-Circuit Missing Values 257 28.2 Equality and Comparison Operators 257 28.3 Logical operators 258 28.4 Control Flow and Short-Circuiting Operators 260 28.5 Arrays With Missing Values 260 28.6 Skipping Missing work in Julia? 47.7 Memory Why does x += y allocate memory when x and y are arrays? 47.8 Asynchronous IO and concurrent synchronous writes Why do concurrent writes to the same stream result in inter-mixed

15.16 Dot Syntax for Vectorizing Functions ..... 92 15.17 Further Reading ..... 94 16 Control Flow ..... 95 16.1 Compound Expressions ..... 95 16.2 Conditional Evaluation ..... 96 16.3 Short-Circuit Missing Values 255 27.2 Equality and Comparison Operators 255 27.3 Logical operators 256 27.4 Control Flow and Short-Circuiting Operators 258 27.5 Arrays With Missing Values 258 27.6 Skipping Missing Julia? 424 46.7 Memory 424 Why does x += y allocate memory when x and y are arrays? 424 46.8 Asynchronous IO and concurrent synchronous writes 425 Why do concurrent writes to the same stream result