Word search completer

Add the following line in the dependencies section inside the pubspec.yaml file:dependencies: webview_flutter: ^1.0.7This package provides a WebView widget to be used in the Flutter ecosystem. It helps to run webpages inside the Flutter application on both Android and iOS devices. While installing this plugin, check that the minSdkVersion in the ./android/app/build.gardle should be greater than or equal to 19:minSdkVersion 19Creating a Web View ScreenNow, we are going to create a Web View screen that will browse the website with the help of the WebView widget. First, we need to create a file called WebViewPage.dart inside the ./lib/screens folder. Then inside the WebViewPage.dart file, we can implement the WebView code as shown in the code snippet below:import 'dart:async';import 'package:flutter/material.dart';import 'package:webview_flutter/webview_flutter.dart';class WebViewPage extends StatelessWidget { final String url; WebViewPage({ @required this.url, }); final Completer _controller = Completer(); @override Widget build(BuildContext context) { return Scaffold( body: WebView( initialUrl: url, javascriptMode: JavascriptMode.unrestricted, onWebViewCreated: (WebViewController webViewController) { _controller.complete(webViewController); }, ), ); }}Here, we have created a stateless widget class that takes url as a parameter value. This widget class returns the Scaffold widget with the WebView widget as its body. We also have initialized a WebViewController that handles the activities and process of web page loading in the WebView widget. Now in the RaisedButton widget in HomePage.dart file, we can add the code to navigate to WebViewPage screen. For that, we need to use the Navigator method on the onPressed event of the RaisedButton widget as shown in the code snippet below:class _HomePageState extends

Read performance is lower than writes for thread counts from 16 to 128 and then the read performance starts scaling. This is because while a PCIe read operation is a Non-Posted Operation, requiring both a request and a completion, a PCIe write operation is a fire and forget operation. Once the Transaction Layer Packet is handed over to the Data Link Layer, the operation completes. A write operation is a "Posted" operation that consists of a request only. Read throughput is typically lower than the write throughput because reads require two transactions instead of a single write for the same amount of data. The PCI Express uses a split transaction model for reads. The read transaction includes the following steps: The requester sends a Memory Read Request (MRR). The completer sends out the acknowledgement to MRR. The completer returns a Completion with Data. The read throughput depends on the delay between the time the read request is issued and the time the completer takes to return the data. However, when the application issues enough number of read requests to cover this delay, then throughput is maximized. That is the reason why while the read performance is less than that of the writes from 16 threads to 128 threads, we measure an increased throughput when the number of requests increases. A lower throughput is measured when the requester waits for completion before issuing subsequent requests. A higher throughput is registered when multiple requests are issued to amortize the delay after the first data returns. Random Writes and Reads N-N To evaluate random IO performance, IOzone was used in the random mode. Tests were conducted on thread counts starting from 4 threads to up to 1024 threads. Direct IO option (-I) was used to run IOzone so that all operations bypass the buffer cache and go directly to the disk. BeeGFS stripe count of 3 and chunk size of 2MB was used. A 4KiB request size is used on IOzone. Performance is measured in I/O operations per second (IOPS). The OS caches were dropped between the runs on the BeeGFS servers as well as BeeGFS clients. The command used for executing the random writes and reads is given below: Random reads and writes: iozone -i 2 -w -c -O -I -r 4K -s $Size -t $Thread -+n -+m /path/to/threadlist Figure 10: Random Read and Write Performance using IOzone wth 8TB aggregate file sizeThe random writes peak at ~3.6 Million IOPS at 512 threads and the random reads peak at ~3.5 Million IOPS at 1024 threads as shown in Figure 10. Both the write and read performance show a higher performance when there are a higher number of IO requests. This is because

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