Massive | A small , happy , dynamic MicroORM for .NET that will love
kandi X-RAY | Massive Summary
kandi X-RAY | Massive Summary
Massive was started by Rob Conery and [has been transfered] to Frans Bouma on March 4th, 2015. It’s a small MicroORM based on the Expando or dynamic type and allows you to work with your database with almost no effort. The design is based on the idea that the code provided to you in this repository is a start: you get up and running in no-time and from there edit and alter it as you see fit.
Support
Quality
Security
License
Reuse
Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of Massive
Massive Key Features
Massive Examples and Code Snippets
Community Discussions
Trending Discussions on Massive
QUESTION
I have implemented a Convolutional Neural Network in C and have been studying what parts of it have the longest latency.
Based on my research, the massive amounts of matricial multiplication required by CNNs makes running them on CPUs and even GPUs very inefficient. However, when I actually profiled my code (on an unoptimized build) I found out that something other than the multiplication itself was the bottleneck of the implementation.
After turning on optimization (-O3 -march=native -ffast-math, gcc cross compiler), the Gprof result was the following:
Clearly, the convolution2D function takes the largest amount of time to run, followed by the batch normalization and depthwise convolution functions.
The convolution function in question looks like this:
...ANSWER
Answered 2022-Mar-10 at 13:57Looking at the result of Cachegrind, it doesn't look like the memory is your bottleneck. The NN has to be stored in memory anyway, but if it's too large that your program's having a lot of L1 cache misses, then it's worth thinking to try to minimize L1 misses, but 1.7% of L1 (data) miss rate is not a problem.
So you're trying to make this run fast anyway. Looking at your code, what's happening at the most inner loop is very simple (load-> multiply -> add -> store), and it doesn't have any side effect other than the final store. This kind of code is easily parallelizable, for example, by multithreading or vectorizing. I think you'll know how to make this run in multiple threads seeing that you can write code with some complexity, and you asked in comments how to manually vectorize the code.
I will explain that part, but one thing to bear in mind is that once you choose to manually vectorize the code, it will often be tied to certain CPU architectures. Let's not consider non-AMD64 compatible CPUs like ARM. Still, you have the option of MMX, SSE, AVX, and AVX512 to choose as an extension for vectorized computation, and each extension has multiple versions. If you want maximum portability, SSE2 is a reasonable choice. SSE2 appeared with Pentium 4, and it supports 128-bit vectors. For this post I'll use AVX2, which supports 128-bit and 256-bit vectors. It runs fine on your CPU, and has reasonable portability these days, supported from Haswell (2013) and Excavator (2015).
The pattern you're using in the inner loop is called FMA (fused multiply and add). AVX2 has an instruction for this. Have a look at this function and the compiled output.
QUESTION
Starting in iOS13, one can monitor the progress of an OperationQueue using the progress property. The documentation states that only operations that do not override start() count when tracking progress. However, asynchronous operations must override start() and not call super() according to the documentation.
Does this mean asynchronous operations and progress are mutually exclusive (i.e. only synchronous operations can be used with progress)? This seems like a massive limitation if this is the case.
In my own project, I removed my override of start() and everything appears to work okay (e.g. dependencies are only started when isFinished is set to true on the dependent operation internally in my async operation base class). BUT, this seems risky since Operation explicitly states to override start().
Thoughts?
Documentaiton references:
https://developer.apple.com/documentation/foundation/operationqueue/3172535-progress
By default, OperationQueue doesn’t report progress until totalUnitCount is set. When totalUnitCount is set, the queue begins reporting progress. Each operation in the queue contributes one unit of completion to the overall progress of the queue for operations that are finished by the end of main(). Operations that override start() and don’t invoke super don’t contribute to the queue’s progress.
https://developer.apple.com/documentation/foundation/operation/1416837-start
If you are implementing a concurrent operation, you must override this method and use it to initiate your operation. Your custom implementation must not call super at any time. In addition to configuring the execution environment for your task, your implementation of this method must also track the state of the operation and provide appropriate state transitions.
Update: I ended up ditching my AysncOperation for a simple SyncOperation that waits until finish() is called (using a semaphore).
ANSWER
Answered 2022-Feb-03 at 20:53You are combining two different but related concepts; asynchronous and concurrency.
An OperationQueue always dispatches Operations onto a separate thread so you do not need to make them explicitly make them asynchronous and there is no need to override start(). You should ensure that your main() does not return until the operation is complete. This means blocking if you perform asynchronous tasks such as network operations.
It is possible to execute an Operation directly. In the case where you want concurrent execution of those operations you need to make them asynchronous. It is in this situation that you would override start()
If you want to implement a concurrent operation—that is, one that runs asynchronously with respect to the calling thread—you must write additional code to start the operation asynchronously. For example, you might spawn a separate thread, call an asynchronous system function, or do anything else to ensure that the start method starts the task and returns immediately and, in all likelihood, before the task is finished.
Most developers should never need to implement concurrent operation objects. If you always add your operations to an operation queue, you do not need to implement concurrent operations. When you submit a nonconcurrent operation to an operation queue, the queue itself creates a thread on which to run your operation. Thus, adding a nonconcurrent operation to an operation queue still results in the asynchronous execution of your operation object code. The ability to define concurrent operations is only necessary in cases where you need to execute the operation asynchronously without adding it to an operation queue.
In summary, make sure your operations are synchronous and do not override start if you want to take advantage of progress
Update
While the normal advice is not to try and make asynchronous tasks synchronous, in this case it is the only thing you can do if you want to take advantage of progress. The problem is that if you have an asynchronous operation, the queue cannot tell when it is actually complete. If the queue can't tell when an operation is complete then it can't update progress accurately for that operation.
You do need to consider the impact on the thread pool of doing this.
The alternative is not to use the inbuilt progress feature and create your own property that you update from your tasks.
QUESTION
I have been struggling with a performance problem in a React (React Native to be exact) app for days. It boils down to this problem:
When a Parent function component has another function component as the Child, the Parent will always re-renders whenever its own parent (GrandParent) re-renders. And this is true even if all components are memoized with React.memo.
It seems to be a fundamental problem for React, because in this common situation, HeavyParent will always re-renders whenever LightGrandParent re-renders, even if neither HeavyParent nor LightChild needs re-rendering. This is obviously causing a massive performance problem for our app.
ANSWER
Answered 2022-Jan-31 at 19:37In the structure you pasted witch is right below
QUESTION
I am currently trying to crawl headlines of the news articles from https://7news.com.au/news/coronavirus-sa.
After I found all headlines are under h2 classes, I wrote following code:
...ANSWER
Answered 2021-Dec-20 at 08:56Your selection is just too general, cause it is selecting all
.decompose() to fix the issue.
How to fix?
Select the headlines mor specific:
QUESTION
Yesterday i pushed the base image layer for my app that contained the environment needed to run my_app.
That push was massive but it is done and up in my repo.
This is currently the image situation in my local machine:
...ANSWER
Answered 2021-Nov-26 at 13:41docker push pushes all layers (5 at the time by default) of the image that are not equal to the image in the repository (aka the layers that did not change), not a single layer, in the end resulting in a new image in your repository.
You can see it as if Docker made a diff between the local and the remote image and pushed only the differences between those two, which will end up being a new image - equal to the one you have in your machine but with "less work" to reach the desired result since it doesn't need to push literally all the layers.
In your case it's taking a lot of time since the 4 Gb layer changed (since the content of what you are copying is different now), making Docker push a big part of the size of your image.
Link for the docker push documentation, if needed: https://docs.docker.com/engine/reference/commandline/push/
QUESTION
is it possible to group by the last 15 days using Java's Collectors.groupingBy?
Input:
...ANSWER
Answered 2021-Nov-18 at 19:19You can get the day difference between two LocalDateTimes using ChronoUnit.DAYS.between(from,to) as stated here.
You can then divide this by 15 (so you have the same number for all days in that range):
QUESTION
I've written a simple Servant application that stores some information in an SQLite db file. Also, I created a generic function that runs a DB query:
...ANSWER
Answered 2021-Nov-03 at 20:24I believe your problem is caused by a lack of understanding of monads. There are plenty of tutorials on the web, so allow me to simplify the issue and explain it in the context of your code.
When in Haskell we write x :: Int, we mean that x is an integer value. In the definition of x we can write
QUESTION
Imagine an asynchronous aiohttp web application that is supported by a Postgresql database connected via asyncpg and does no other I/O. How can I have a middle-layer hosting the application logic, that is not async? (I know I can simply make everything async -- but imagine my app to have massive application logic, only bound by database I/O, and I cannot touch everything of it).
Pseudo code:
...ANSWER
Answered 2021-Oct-27 at 04:00You need to create a secondary thread where you run your async code. You initialize the secondary thread with its own event loop, which runs forever. Execute each async function by calling run_coroutine_threadsafe(), and calling result() on the returned object. That's an instance of concurrent.futures.Future, and its result() method doesn't return until the coroutine's result is ready from the secondary thread.
Your main thread is then, in effect, calling each async function as if it were a sync function. The main thread doesn't proceed until each function call is finished. BTW it doesn't matter if your sync function is actually running in an event loop context or not.
The calls to result() will, of course, block the main thread's event loop. That can't be avoided if you want to get the effect of running an async function from sync code.
Needless to say, this is an ugly thing to do and it's suggestive of the wrong program structure. But you're trying to convert a legacy program, and it may help with that.
QUESTION
I'm rendering at many hundreds of frames per second. Turning vsync on is not desirable because the game is an FPS.
For some reason I do not understand, on any modern GPU (any discrete GPU in the last 7 or so years) it renders flawlessly, fast, and smooth.
However, if done on any integrated GPU or older GPU, there's massive stuttering that happens to the point of it being unplayable. Further, there seems to be a 100ms delay that users feel.
For some reason, if I do GL.Finish() immediately after a SwapBuffers(), this problem is strongly mitigated for integrated/older GPUs.
Why is this?
It makes no sense to me that calling GL.Finish() after swapping the buffers would do anything, because I thought the rendering commands need to be executed completely before swapping the buffers so that the monitor can get all of the drawing commands issued before the swap.
ANSWER
Answered 2021-Oct-08 at 14:23Swapping the default framebuffer may cause a pipeline flush, but it also may decide not to do so. [Reference]
There is not even a guarantee that SwapBuffer really waits until the buffer swapping has finished. Some implementations may decide to only enqueue the buffer swap in the command queue and return immediately after that. So in case the GPU doesn't flush on a swap, GL.Finish will flush the pipeline.
You might also want to read this thread: https://community.khronos.org/t/swapbuffers-and-synchronization/107667 since it discusses the topic in more detail.
QUESTION
I am making a program where I want to take an image and reduce its color palette to a preset palette of 60 colors, and then add a dithering effect. This seems to involve two things:
- A color distance algorithm that goes through each pixel, gets its color, and then changes it to the color closest to it in the palette so that that image doesn't have colors that are not contained in the palette.
- A dithering algorithm that goes through the color of each pixel and diffuses the difference between the original color and the new palette color chosen across the surrounding pixels.
After reading about color difference, I figured I would use either the CIE94 or CIEDE2000 algorithm for finding the closest color from my list. I also decided to use the fairly common Floyd–Steinberg dithering algorithm for the dithering effect.
Over the past 2 days I have written my own versions of these algorithms, pulled other versions of them from examples on the internet, tried them both first in Java and now C#, and pretty much every single time the output image has the same issue. Some parts of it look perfectly fine, have the correct colors, and are dithered properly, but then other parts (and sometimes the entire image) end up way too bright, are completely white, or all blur together. Usually darker images or darker parts of images turn out fine, but any part that is bright or has lighter colors at all gets turned up way brighter. Here is an example of an input and output image with these issues:
Input:
]3
Output:
I do have one idea for what may be causing this. When a pixel is sent through the "nearest color" function, I have it output its RGB values and it seems like some of them have their R value (and potentially other values??) pushed way higher than they should be, and even sometimes over 255 as shown in the screenshot. This does NOT happen for the earliest pixels in the image, only for ones that are multiple pixels in already and are already somewhat bright. This leads me to believe it is the dithering/error algorithm doing this, and not the color conversion or color difference algorithms. If that is the issue, then how would I go about fixing that?
Here's the relevant code and functions I'm using. At this point it's a mix of stuff I wrote and stuff I've found in libraries or other StackOverflow posts. I believe the main dithering algorithm and C3 class are copied basically directly from this Github page (and changed to work with C#, obviously)
...ANSWER
Answered 2021-Sep-19 at 07:08It appears that when you shift the error to the neighbors in floydSteinbergDithering() the r,g,b values never get clamped until you cast them back to Color.
Since you're using int and not byte there is no prevention of overflows to negative or large values greater than 255 for r, g, and b.
You should consider implementing r,g, and b as properties that clamp to 0-255 when they're set.
This will ensure their values will never be outside your expected range (0 - 255).
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Massive
Massive.Shared.cs
Massive.YourDatabase.cs, e.g. Massive.SqlServer.cs for SQL Server
Massive.Shared.Async.cs, if you want to use the Massive API asynchronously. Requires .NET 4.5 or higher.
Support
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
