Tutorial by Examples: e

Image img = new Image(); BitmapImage bitmap = new BitmapImage(new Uri("ms-appx:///Path-to-image-in-solution-directory", UriKind.Absolute)); img.Source = bitmap;

public override async void ViewDidLoad(){ base.ViewDidLoad(); // Perform any additional setup after loading the view, typically from a nib. Title = "Pull to Refresh Sample"; table = new UITableView(new CGRect(0, 20, View.Bounds.Width, View.Bounds.Height - 20)); //table.Aut...

drop table table01; drop table table02; create table table01 ( code int, name varchar(50), old int ); create table table02 ( code int, name varchar(50), old int ); truncate table table01; insert into table01 values (1, 'A', 10); insert in...

The simplest approach to parallel reduction in CUDA is to assign a single block to perform the task: static const int arraySize = 10000; static const int blockSize = 1024; __global__ void sumCommSingleBlock(const int *a, int *out) { int idx = threadIdx.x; int sum = 0; for (int i ...

Doing parallel reduction for a non-commutative operator is a bit more involved, compared to commutative version. In the example we still use a addition over integers for the simplicity sake. It could be replaced, for example, with matrix multiplication which really is non-commutative. Note, when ...

Multi-block approach to parallel reduction in CUDA poses an additional challenge, compared to single-block approach, because blocks are limited in communication. The idea is to let each block compute a part of the input array, and then have one final block to merge all the partial results. To do t...

Multi-block approach to parallel reduction is very similar to the single-block approach. The global input array must be split into sections, each reduced by a single block. When a partial result from each block is obtained, one final block reduces these to obtain the final result. sumNoncommSin...

Sometimes the reduction has to be performed on a very small scale, as a part of a bigger CUDA kernel. Suppose for example, that the input data has exactly 32 elements - the number of threads in a warp. In such scenario a single warp can be assigned to perform the reduction. Given that warp execut...

Sometimes the reduction has to be performed on a very small scale, as a part of a bigger CUDA kernel. Suppose for example, that the input data has exactly 32 elements - the number of threads in a warp. In such scenario a single warp can be assigned to perform the reduction. Given that warp execut...

Typically, reduction is performed on global or shared array. However, when the reduction is performed on a very small scale, as a part of a bigger CUDA kernel, it can be performed with a single warp. When that happens, on Keppler or higher architectures (CC>=3.0), it is possible to use warp-shu...

That the easiest case actually, very natural in the React world and the chances are - you are already using it. You can pass props down to child components. In this example message is the prop that we pass down to the child component, the name message is chosen arbitrarily, you can name it anything...

Go to Catalog > Filters and select Insert to create a filter group. Assign a filter group name (e.g. Color) and add filter name values (e.g. Blue, Red, Yellow).

Go to Catalog > Categories and Edit a category. Under the Data tab add the filters you want to be able to apply to that category (e.g. Color > Blue, Color > Red).

Go to Catalog > Products and Edit a product. Under the Links tab add the filters which apply to the product (e.g. Color > Blue). Apply to as many products as applicable.

Go to Extensions > Modules > Filter. If not installed select Install. Click Edit & then Enabled from option & then Save module.

Go to Design > Layout > Edit Category Page and Set whatever position and sort order you would like. and then save.

interface IMyDirectiveController { // specify exposed controller methods and properties here getUrl(): string; } class MyDirectiveController implements IMyDirectiveController { // Inner injections, per each directive public static $inject = ["$location", "...

export function myDirective($location: ng.ILocationService): ng.IDirective { return { link: (scope: ng.IScope, element: ng.IAugmentedJQuery, attributes: ng.IAttributes): void => { element.text("Current URL: " + $location.url()); ...

By selecting a matrix and choosing "Insert Table" from the menu, you create a table which allows you to pull and insert data in a structured way. Let's say you have named the table "SalesEvents" and given that the first (header) row reads "Salesperson" "Date" ...

When you have an Excel Table, and not only then, it is easy to use data as input in a PivotTable which will provide most of the analysis you would need on it. Learn to use it you won't regret it! It could replaces tons of user designed cell Formulas and it is fast and much easier to document.