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MediaSPIP version 0.1 Beta
16 avril 2011, parMediaSPIP 0.1 beta est la première version de MediaSPIP décrétée comme "utilisable".
Le fichier zip ici présent contient uniquement les sources de MediaSPIP en version standalone.
Pour avoir une installation fonctionnelle, il est nécessaire d’installer manuellement l’ensemble des dépendances logicielles sur le serveur.
Si vous souhaitez utiliser cette archive pour une installation en mode ferme, il vous faudra également procéder à d’autres modifications (...) -
MediaSPIP 0.1 Beta version
25 avril 2011, parMediaSPIP 0.1 beta is the first version of MediaSPIP proclaimed as "usable".
The zip file provided here only contains the sources of MediaSPIP in its standalone version.
To get a working installation, you must manually install all-software dependencies on the server.
If you want to use this archive for an installation in "farm mode", you will also need to proceed to other manual (...) -
Amélioration de la version de base
13 septembre 2013Jolie sélection multiple
Le plugin Chosen permet d’améliorer l’ergonomie des champs de sélection multiple. Voir les deux images suivantes pour comparer.
Il suffit pour cela d’activer le plugin Chosen (Configuration générale du site > Gestion des plugins), puis de configurer le plugin (Les squelettes > Chosen) en activant l’utilisation de Chosen dans le site public et en spécifiant les éléments de formulaires à améliorer, par exemple select[multiple] pour les listes à sélection multiple (...)
Sur d’autres sites (12306)
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How to Increase Conversions With Form Analysis
30 janvier 2024, par ErinForms are one of the most important elements of your website. They are also one of the most difficult elements to analyse and improve.
Unlike a webpage, forms aren’t all that easy to analyse with standard web analytics tools. You need to learn how to conduct form analysis if you want to improve your forms’ conversion rates and increase revenue.
In this article, we’ll explain what form analysis is and why conducting a thorough form analysis is so important.
What is form analysis ?
Form analysis is a process that measures the effectiveness of your forms. Form analysis uses several tools and techniques like a form analytics platform, heatmaps, and session recordings to collect user data and understand how visitors behave when filling in forms.
The goal is to improve the design and effectiveness of your forms, reducing abandonment rate and encouraging more users to submit them.
There are plenty of reasons visitors could be having trouble with your forms, from confusing form fields to poor design and lengthy verification processes. Form analytics can help you pinpoint why your form’s conversion rate is so low or why so many users abandon your form halfway through filling it in.
Why is form analysis important ?
Website forms have some of the highest bounce rates and abandonments of any website element. By analysing your forms, you can achieve the following outcomes :
Reduce form abandonment
When it’s tough enough to get users to start filling in your form, the last thing you want them to do is abandon it halfway through. But that’s probably what your users are doing more than you’d like to think.
Why are they abandoning it ? Even if you’re humble enough to admit you didn’t create the greatest form the world’s ever seen, it can still be incredibly difficult to pin down why users give up on your form.
That’s unless you conduct a form analysis. By analysing metrics and user behaviour, you can pinpoint and rectify the issues that cause users to abandon your form.
Improve the user experience
Best practices will only take you so far. How users behave when filling in a form on your website may be completely different to how they behave on another site. That’s why you need to use form analysis to understand how users behave specifically on your website — and then use that information to optimise the design, layout, and content of the form to better suit them.
If one field is regularly left empty, for example, you can delete it. If users spend several minutes filling out a form with a high abandonment rate, you could shorten it.
The goal isn’t to make the best form ever but to make the best form for your audience.
Increase conversions
Ultimately, form analysis helps you improve your form’s most important metric : conversions. Reducing your abandonment rate will naturally lead to more completions, but so will taking advantage of other optimisation opportunities that only become clear with form analysis. This can include optimisations like :
- Moving the form higher up on the page
- Shortening the form
- Changing the heading and CTAs
- Renaming field labels
A thorough form analysis process can ensure your forms generate as many conversions as possible.
Why do users abandon forms ?
Are you already suffering from high form abandonment rates ? Don’t worry, you’re not alone. Marketers regularly make the same mistakes when creating forms that cause users to give up halfway through completion.
Here are some of the most common reasons for form abandonment :
- There are too many steps. If you’re telling users they’ve just completed step 2 of 12, you can bet they won’t bother finishing your form.
- They ask for too much information. No one wants to fill out a long form, and often, users won’t have the information on hand if you ask for too much. Just look at the rate left blank from the Unneeded Fields report in the screenshot below :
- The form is confusing. Unclear form fields or directions can put users off.
- All the fields are free text and time-consuming. Filling out forms with long text fields takes too much time. To speed things up, use dropdown options in the fields, but keep the options to a minimum. This not only helps users finish the form faster but also makes it easier to analyse the data later because it keeps the data format consistent so you can organise the information more efficiently.
- Users don’t trust the form. This is a particular problem on checkout pages where users are entering sensitive information.
How to conduct form analysis
You need to collect user behaviour data to effectively analyse your forms. But a lot of traditional website analytics tools won’t have the required functionality.
Matomo is different. Our web analytics solution offers comprehensive web analytics as well as additional features like Heatmaps, Session Recordings, A/B Testing, and Form Analytics to provide all the functionality you need.
Now if you don’t use Matomo, you can try it free for 21 days (no credit card required) to see if it’s the right tool for you.
Whether you use Matomo or not is up to you. But, once you have a suitable tool in place, just follow the steps below to conduct a form analysis.
Check your analytics
Tracking and analysing specific form metrics should be the first place you start. We recommend collecting data on the following metrics :
- Form starter rate : the percentage of visitors who actually start to fill in your form
- Completion rate : the percentage of visitors who complete the form
- Form abandonment rate : the percentage of users who gave up filling in your form
- Time spent completing your form : the average length of time users spend on your form
Let’s look at these metrics are in Matomo’s Form Analytics :
The dashboard shows an overview of these metrics over a given period, allowing you to see at a glance whether there are issues you need to rectify.
Next, deep dive into the performance of each form to see things like :
- Drop off fields
- Unused fields
- Entry field
- Most corrected fields
You can even use Matomo’s visitor log to see who’s behind every submission.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Use a heatmap
A heatmap is a colour-based graphical representation of data. A heatmap will show what users to do on your website, including :
- How far they scroll
- Which buttons they click on
- Where they focus their attention
When used on a webpage with a form, you’ll be able to see how often users interact with your form based on the heatmap colour, with warmer colours representing greater engagement levels.
Let’s look at a heatmap in Matomo :
This heatmap is showing us how far down users have scrolled. It’s clear that only 63% of visitors are reaching the point above our call to action to see all features. We might want to consider moving that call to action up in order to get more engagement.
A heatmap is a great way to see whether your form’s placement gets the level of attention you want from visitors and to what extent visitors interact with your field.
Record user sessions
Session replays go even further than heatmaps, recording a real-life user interacting with your site. It’s like looking over a visitor’s shoulder while they use your site.
With Matomo, you can record any sessions where the user takes a certain action (like starting to fill in a form), allowing you to build a rich library of qualitative data.
You can then replay a recorded session at your leisure to understand exactly how users interact with your forms.
Segment users
If you really want to understand how visitors use your forms, then it’s essential to segment your data.
You can segment all Form Analytics reports by over 100 pre-built segments in Matomo.
One way to segment your data is by comparing the average time on form of those who completed the form with those who abandoned it.
If users abandon a form quickly, that could indicate your form is irrelevant to this audience or too long. If users spend a lot of time on the form, however, it’s probably safe to assume that it is relevant but there is something wrong with the form itself.
Looking at the Field Timings report will help you pinpoint which field visitors are spending the most time on and causing frustration.
The Field Timings example report in Matomo above, it’s evident that the “Overview of your needs” field takes up the most time (avg. time spent is 1 min 40s). To improve this, we might want to change it to a dropdown field. This way, users can quickly select options, and if necessary, provide additional details.
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Get the web insights you need, without compromising data accuracy.
Another way is to segment data by traffic source and compare each source’s conversion rate. This will show whether one traffic source converts better than another or if one source isn’t interested in your form at all.
How to optimise web forms
Want to implement what you’ve learnt from your form analysis ? Follow these steps to optimise your existing web forms.
Define your form’s purpose
The first step in optimising your existing web forms is to give a clear and definitive purpose to every single one.
When you have a defined goal, creating a form users will complete is much easier. After all, if you don’t know why people should fill in one of your forms, how would a visitor possibly know ?
Take a look at one of our forms below :
The purpose of this form is to get users to sign up for a free trial of our web analytics platform, and every element works towards that goal :
- The headline directs the user to take action
- The copy explains that it’s a free trial that doesn’t require credit card details
- The green call-to-action button reinforces the action and benefit
- There is validation to support this under the form – “Trusted on over 1 million websites in over 190+ countries”
Our clear instructions leave users no doubt about why they should fill in the form or what will happen.
Choose the right type of form
You can use several forms on your website, each with different designs, form fields, and goals.
For example :
- Registration forms are fairly minimalist and designed to collect the least amount of data possible.
- Contact forms are concise so that it’s easy for potential customers to reach your team.
- Checkout forms balance a need to collect important data with a streamlined design that doesn’t put users off.
- Lead generation forms are compelling and usually include qualifying questions so sales teams can score leads.
Make sure you are using the right type of form to avoid abandonments and other issues. For example, requiring users to fill in a lengthy lead generation-style form when you want them to sign up for a free trial will probably kill your conversion rate.
Test form elements
If your form analysis has shed light on one or two issues, you can use A/B or multivariate testing to trial new elements or designs and see how they compare.
There’s no shortage of elements you can test, including the form’s :
- Headline
- Placement
- Design
- CTA button
- Colour-scheme
- Length
- Form fields
Matomo makes it easy to create and run A/B tests on your website’s forms.
Move your form above the fold
One of the simplest ways to optimise your web form is to move it above the fold — that’s the section of the screen users see when they load your page.
Why ? Well, the more people who see your form, the more people will fill it in. And when it’s above the fold, users can’t help but see it.
Conclusion
Forms are one of the most important elements on your website, so why not treat them as such and regularly run a thorough form analysis ? By doing so, you’ll identify ways to optimise your form, improve the user experience, and improve conversions.
Matomo is the best platform for conducting form analysis. Our combination of web analytics, Form Analytics, Session Recordings, and Heatmaps means you have all the tools you need to learn exactly how visitors interact with your forms.
See just how powerful Matomo’s tools are by starting a free 21-day trial, no credit card required.
Try Matomo for Free
21 day free trial. No credit card required.
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avcodec/x86/vvc : add avg and avg_w AVX2 optimizations
23 janvier 2024, par Wu Jianhuaavcodec/x86/vvc : add avg and avg_w AVX2 optimizations
The avg/avg_w is based on dav1d.
See https://code.videolan.org/videolan/dav1d/-/blob/master/src/x86/mc_avx2.asmvvc_avg_8_2x2_c : 71.6
vvc_avg_8_2x2_avx2 : 26.8
vvc_avg_8_2x4_c : 140.8
vvc_avg_8_2x4_avx2 : 34.6
vvc_avg_8_2x8_c : 410.3
vvc_avg_8_2x8_avx2 : 41.3
vvc_avg_8_2x16_c : 769.3
vvc_avg_8_2x16_avx2 : 60.3
vvc_avg_8_2x32_c : 1669.6
vvc_avg_8_2x32_avx2 : 105.1
vvc_avg_8_2x64_c : 1978.3
vvc_avg_8_2x64_avx2 : 425.8
vvc_avg_8_2x128_c : 6536.8
vvc_avg_8_2x128_avx2 : 1315.1
vvc_avg_8_4x2_c : 155.6
vvc_avg_8_4x2_avx2 : 26.1
vvc_avg_8_4x4_c : 250.3
vvc_avg_8_4x4_avx2 : 31.3
vvc_avg_8_4x8_c : 831.8
vvc_avg_8_4x8_avx2 : 41.3
vvc_avg_8_4x16_c : 1461.1
vvc_avg_8_4x16_avx2 : 57.1
vvc_avg_8_4x32_c : 2821.6
vvc_avg_8_4x32_avx2 : 105.1
vvc_avg_8_4x64_c : 3615.8
vvc_avg_8_4x64_avx2 : 412.6
vvc_avg_8_4x128_c : 11962.6
vvc_avg_8_4x128_avx2 : 1274.3
vvc_avg_8_8x2_c : 215.8
vvc_avg_8_8x2_avx2 : 29.1
vvc_avg_8_8x4_c : 430.6
vvc_avg_8_8x4_avx2 : 37.6
vvc_avg_8_8x8_c : 1463.3
vvc_avg_8_8x8_avx2 : 51.8
vvc_avg_8_8x16_c : 2630.1
vvc_avg_8_8x16_avx2 : 97.6
vvc_avg_8_8x32_c : 5813.8
vvc_avg_8_8x32_avx2 : 196.6
vvc_avg_8_8x64_c : 6687.3
vvc_avg_8_8x64_avx2 : 487.8
vvc_avg_8_8x128_c : 13178.6
vvc_avg_8_8x128_avx2 : 1290.6
vvc_avg_8_16x2_c : 443.8
vvc_avg_8_16x2_avx2 : 28.3
vvc_avg_8_16x4_c : 1253.3
vvc_avg_8_16x4_avx2 : 32.1
vvc_avg_8_16x8_c : 2236.3
vvc_avg_8_16x8_avx2 : 44.3
vvc_avg_8_16x16_c : 5127.8
vvc_avg_8_16x16_avx2 : 63.3
vvc_avg_8_16x32_c : 6573.3
vvc_avg_8_16x32_avx2 : 223.6
vvc_avg_8_16x64_c : 30311.8
vvc_avg_8_16x64_avx2 : 437.8
vvc_avg_8_16x128_c : 25693.3
vvc_avg_8_16x128_avx2 : 1266.8
vvc_avg_8_32x2_c : 954.6
vvc_avg_8_32x2_avx2 : 32.1
vvc_avg_8_32x4_c : 2359.6
vvc_avg_8_32x4_avx2 : 39.6
vvc_avg_8_32x8_c : 5703.6
vvc_avg_8_32x8_avx2 : 57.1
vvc_avg_8_32x16_c : 9967.6
vvc_avg_8_32x16_avx2 : 107.1
vvc_avg_8_32x32_c : 21327.6
vvc_avg_8_32x32_avx2 : 272.6
vvc_avg_8_32x64_c : 39240.8
vvc_avg_8_32x64_avx2 : 529.6
vvc_avg_8_32x128_c : 52580.8
vvc_avg_8_32x128_avx2 : 1338.8
vvc_avg_8_64x2_c : 1647.3
vvc_avg_8_64x2_avx2 : 38.8
vvc_avg_8_64x4_c : 5130.1
vvc_avg_8_64x4_avx2 : 58.8
vvc_avg_8_64x8_c : 6529.3
vvc_avg_8_64x8_avx2 : 88.3
vvc_avg_8_64x16_c : 19913.6
vvc_avg_8_64x16_avx2 : 162.3
vvc_avg_8_64x32_c : 39360.8
vvc_avg_8_64x32_avx2 : 295.8
vvc_avg_8_64x64_c : 49658.3
vvc_avg_8_64x64_avx2 : 784.1
vvc_avg_8_64x128_c : 108513.1
vvc_avg_8_64x128_avx2 : 1977.1
vvc_avg_8_128x2_c : 3226.1
vvc_avg_8_128x2_avx2 : 61.1
vvc_avg_8_128x4_c : 10280.3
vvc_avg_8_128x4_avx2 : 94.6
vvc_avg_8_128x8_c : 18079.3
vvc_avg_8_128x8_avx2 : 155.3
vvc_avg_8_128x16_c : 45121.8
vvc_avg_8_128x16_avx2 : 285.3
vvc_avg_8_128x32_c : 48651.8
vvc_avg_8_128x32_avx2 : 581.6
vvc_avg_8_128x64_c : 165078.6
vvc_avg_8_128x64_avx2 : 1942.8
vvc_avg_8_128x128_c : 339103.1
vvc_avg_8_128x128_avx2 : 4332.6
vvc_avg_10_2x2_c : 144.3
vvc_avg_10_2x2_avx2 : 26.8
vvc_avg_10_2x4_c : 142.6
vvc_avg_10_2x4_avx2 : 45.3
vvc_avg_10_2x8_c : 478.1
vvc_avg_10_2x8_avx2 : 38.1
vvc_avg_10_2x16_c : 518.3
vvc_avg_10_2x16_avx2 : 58.1
vvc_avg_10_2x32_c : 2059.8
vvc_avg_10_2x32_avx2 : 93.1
vvc_avg_10_2x64_c : 2383.8
vvc_avg_10_2x64_avx2 : 714.8
vvc_avg_10_2x128_c : 4498.3
vvc_avg_10_2x128_avx2 : 1466.3
vvc_avg_10_4x2_c : 228.6
vvc_avg_10_4x2_avx2 : 26.8
vvc_avg_10_4x4_c : 378.3
vvc_avg_10_4x4_avx2 : 30.6
vvc_avg_10_4x8_c : 866.8
vvc_avg_10_4x8_avx2 : 44.6
vvc_avg_10_4x16_c : 1018.1
vvc_avg_10_4x16_avx2 : 58.1
vvc_avg_10_4x32_c : 3590.8
vvc_avg_10_4x32_avx2 : 128.8
vvc_avg_10_4x64_c : 4200.8
vvc_avg_10_4x64_avx2 : 663.6
vvc_avg_10_4x128_c : 8450.8
vvc_avg_10_4x128_avx2 : 1531.8
vvc_avg_10_8x2_c : 369.3
vvc_avg_10_8x2_avx2 : 28.3
vvc_avg_10_8x4_c : 513.8
vvc_avg_10_8x4_avx2 : 32.1
vvc_avg_10_8x8_c : 1720.3
vvc_avg_10_8x8_avx2 : 49.1
vvc_avg_10_8x16_c : 1894.8
vvc_avg_10_8x16_avx2 : 71.6
vvc_avg_10_8x32_c : 3931.3
vvc_avg_10_8x32_avx2 : 148.1
vvc_avg_10_8x64_c : 7964.3
vvc_avg_10_8x64_avx2 : 613.1
vvc_avg_10_8x128_c : 15540.1
vvc_avg_10_8x128_avx2 : 1585.1
vvc_avg_10_16x2_c : 877.3
vvc_avg_10_16x2_avx2 : 27.6
vvc_avg_10_16x4_c : 955.8
vvc_avg_10_16x4_avx2 : 29.8
vvc_avg_10_16x8_c : 3419.6
vvc_avg_10_16x8_avx2 : 62.6
vvc_avg_10_16x16_c : 3826.8
vvc_avg_10_16x16_avx2 : 54.3
vvc_avg_10_16x32_c : 7655.3
vvc_avg_10_16x32_avx2 : 86.3
vvc_avg_10_16x64_c : 30011.1
vvc_avg_10_16x64_avx2 : 692.6
vvc_avg_10_16x128_c : 47894.8
vvc_avg_10_16x128_avx2 : 1580.3
vvc_avg_10_32x2_c : 944.3
vvc_avg_10_32x2_avx2 : 29.8
vvc_avg_10_32x4_c : 2022.6
vvc_avg_10_32x4_avx2 : 35.1
vvc_avg_10_32x8_c : 6148.8
vvc_avg_10_32x8_avx2 : 51.3
vvc_avg_10_32x16_c : 12601.6
vvc_avg_10_32x16_avx2 : 70.8
vvc_avg_10_32x32_c : 15958.6
vvc_avg_10_32x32_avx2 : 124.3
vvc_avg_10_32x64_c : 31784.6
vvc_avg_10_32x64_avx2 : 757.3
vvc_avg_10_32x128_c : 63892.8
vvc_avg_10_32x128_avx2 : 1711.3
vvc_avg_10_64x2_c : 1890.8
vvc_avg_10_64x2_avx2 : 34.3
vvc_avg_10_64x4_c : 6267.3
vvc_avg_10_64x4_avx2 : 42.6
vvc_avg_10_64x8_c : 12778.1
vvc_avg_10_64x8_avx2 : 67.8
vvc_avg_10_64x16_c : 22304.3
vvc_avg_10_64x16_avx2 : 116.8
vvc_avg_10_64x32_c : 30777.1
vvc_avg_10_64x32_avx2 : 201.1
vvc_avg_10_64x64_c : 60169.1
vvc_avg_10_64x64_avx2 : 1454.3
vvc_avg_10_64x128_c : 124392.8
vvc_avg_10_64x128_avx2 : 3648.6
vvc_avg_10_128x2_c : 3650.1
vvc_avg_10_128x2_avx2 : 41.1
vvc_avg_10_128x4_c : 22887.8
vvc_avg_10_128x4_avx2 : 64.1
vvc_avg_10_128x8_c : 14622.6
vvc_avg_10_128x8_avx2 : 111.6
vvc_avg_10_128x16_c : 62207.6
vvc_avg_10_128x16_avx2 : 186.3
vvc_avg_10_128x32_c : 59761.3
vvc_avg_10_128x32_avx2 : 374.6
vvc_avg_10_128x64_c : 117504.3
vvc_avg_10_128x64_avx2 : 2684.6
vvc_avg_10_128x128_c : 236767.6
vvc_avg_10_128x128_avx2 : 15278.1
vvc_avg_12_2x2_c : 78.6
vvc_avg_12_2x2_avx2 : 26.1
vvc_avg_12_2x4_c : 254.1
vvc_avg_12_2x4_avx2 : 30.6
vvc_avg_12_2x8_c : 261.8
vvc_avg_12_2x8_avx2 : 39.1
vvc_avg_12_2x16_c : 527.6
vvc_avg_12_2x16_avx2 : 57.3
vvc_avg_12_2x32_c : 1089.1
vvc_avg_12_2x32_avx2 : 93.8
vvc_avg_12_2x64_c : 2337.6
vvc_avg_12_2x64_avx2 : 707.1
vvc_avg_12_2x128_c : 4582.1
vvc_avg_12_2x128_avx2 : 1414.6
vvc_avg_12_4x2_c : 129.6
vvc_avg_12_4x2_avx2 : 26.8
vvc_avg_12_4x4_c : 427.3
vvc_avg_12_4x4_avx2 : 30.6
vvc_avg_12_4x8_c : 529.6
vvc_avg_12_4x8_avx2 : 36.6
vvc_avg_12_4x16_c : 1022.1
vvc_avg_12_4x16_avx2 : 57.3
vvc_avg_12_4x32_c : 1987.6
vvc_avg_12_4x32_avx2 : 84.3
vvc_avg_12_4x64_c : 4147.6
vvc_avg_12_4x64_avx2 : 706.3
vvc_avg_12_4x128_c : 8469.3
vvc_avg_12_4x128_avx2 : 1448.3
vvc_avg_12_8x2_c : 253.6
vvc_avg_12_8x2_avx2 : 27.6
vvc_avg_12_8x4_c : 836.3
vvc_avg_12_8x4_avx2 : 32.1
vvc_avg_12_8x8_c : 1074.6
vvc_avg_12_8x8_avx2 : 45.1
vvc_avg_12_8x16_c : 3616.8
vvc_avg_12_8x16_avx2 : 71.6
vvc_avg_12_8x32_c : 3823.6
vvc_avg_12_8x32_avx2 : 140.1
vvc_avg_12_8x64_c : 7764.8
vvc_avg_12_8x64_avx2 : 656.1
vvc_avg_12_8x128_c : 15896.1
vvc_avg_12_8x128_avx2 : 1232.8
vvc_avg_12_16x2_c : 462.1
vvc_avg_12_16x2_avx2 : 26.8
vvc_avg_12_16x4_c : 1732.1
vvc_avg_12_16x4_avx2 : 29.1
vvc_avg_12_16x8_c : 2097.6
vvc_avg_12_16x8_avx2 : 62.6
vvc_avg_12_16x16_c : 6753.1
vvc_avg_12_16x16_avx2 : 47.8
vvc_avg_12_16x32_c : 7373.1
vvc_avg_12_16x32_avx2 : 80.8
vvc_avg_12_16x64_c : 15046.3
vvc_avg_12_16x64_avx2 : 621.1
vvc_avg_12_16x128_c : 52574.6
vvc_avg_12_16x128_avx2 : 1417.1
vvc_avg_12_32x2_c : 1712.1
vvc_avg_12_32x2_avx2 : 29.8
vvc_avg_12_32x4_c : 2036.8
vvc_avg_12_32x4_avx2 : 37.6
vvc_avg_12_32x8_c : 4017.6
vvc_avg_12_32x8_avx2 : 44.1
vvc_avg_12_32x16_c : 8018.6
vvc_avg_12_32x16_avx2 : 70.8
vvc_avg_12_32x32_c : 15637.6
vvc_avg_12_32x32_avx2 : 124.3
vvc_avg_12_32x64_c : 31143.3
vvc_avg_12_32x64_avx2 : 830.3
vvc_avg_12_32x128_c : 75706.8
vvc_avg_12_32x128_avx2 : 1604.8
vvc_avg_12_64x2_c : 3230.3
vvc_avg_12_64x2_avx2 : 33.6
vvc_avg_12_64x4_c : 4139.6
vvc_avg_12_64x4_avx2 : 45.1
vvc_avg_12_64x8_c : 8201.6
vvc_avg_12_64x8_avx2 : 67.1
vvc_avg_12_64x16_c : 25632.3
vvc_avg_12_64x16_avx2 : 110.3
vvc_avg_12_64x32_c : 30744.3
vvc_avg_12_64x32_avx2 : 200.3
vvc_avg_12_64x64_c : 105554.8
vvc_avg_12_64x64_avx2 : 1325.6
vvc_avg_12_64x128_c : 235254.3
vvc_avg_12_64x128_avx2 : 3132.6
vvc_avg_12_128x2_c : 6194.3
vvc_avg_12_128x2_avx2 : 55.1
vvc_avg_12_128x4_c : 7583.8
vvc_avg_12_128x4_avx2 : 79.3
vvc_avg_12_128x8_c : 14635.6
vvc_avg_12_128x8_avx2 : 104.3
vvc_avg_12_128x16_c : 29270.8
vvc_avg_12_128x16_avx2 : 194.3
vvc_avg_12_128x32_c : 60113.6
vvc_avg_12_128x32_avx2 : 346.3
vvc_avg_12_128x64_c : 197030.3
vvc_avg_12_128x64_avx2 : 2779.6
vvc_avg_12_128x128_c : 432809.6
vvc_avg_12_128x128_avx2 : 5513.3
vvc_w_avg_8_2x2_c : 84.3
vvc_w_avg_8_2x2_avx2 : 42.6
vvc_w_avg_8_2x4_c : 156.3
vvc_w_avg_8_2x4_avx2 : 58.8
vvc_w_avg_8_2x8_c : 310.6
vvc_w_avg_8_2x8_avx2 : 73.1
vvc_w_avg_8_2x16_c : 942.1
vvc_w_avg_8_2x16_avx2 : 113.3
vvc_w_avg_8_2x32_c : 1098.8
vvc_w_avg_8_2x32_avx2 : 202.6
vvc_w_avg_8_2x64_c : 2414.3
vvc_w_avg_8_2x64_avx2 : 467.6
vvc_w_avg_8_2x128_c : 4763.8
vvc_w_avg_8_2x128_avx2 : 1333.1
vvc_w_avg_8_4x2_c : 140.1
vvc_w_avg_8_4x2_avx2 : 49.8
vvc_w_avg_8_4x4_c : 276.3
vvc_w_avg_8_4x4_avx2 : 58.1
vvc_w_avg_8_4x8_c : 524.3
vvc_w_avg_8_4x8_avx2 : 72.3
vvc_w_avg_8_4x16_c : 1108.1
vvc_w_avg_8_4x16_avx2 : 111.8
vvc_w_avg_8_4x32_c : 2149.8
vvc_w_avg_8_4x32_avx2 : 199.6
vvc_w_avg_8_4x64_c : 12288.1
vvc_w_avg_8_4x64_avx2 : 509.3
vvc_w_avg_8_4x128_c : 8398.6
vvc_w_avg_8_4x128_avx2 : 1319.6
vvc_w_avg_8_8x2_c : 271.1
vvc_w_avg_8_8x2_avx2 : 44.1
vvc_w_avg_8_8x4_c : 503.3
vvc_w_avg_8_8x4_avx2 : 61.8
vvc_w_avg_8_8x8_c : 1031.1
vvc_w_avg_8_8x8_avx2 : 93.8
vvc_w_avg_8_8x16_c : 2009.8
vvc_w_avg_8_8x16_avx2 : 163.1
vvc_w_avg_8_8x32_c : 4161.3
vvc_w_avg_8_8x32_avx2 : 292.1
vvc_w_avg_8_8x64_c : 7940.6
vvc_w_avg_8_8x64_avx2 : 592.1
vvc_w_avg_8_8x128_c : 16802.3
vvc_w_avg_8_8x128_avx2 : 1287.6
vvc_w_avg_8_16x2_c : 762.6
vvc_w_avg_8_16x2_avx2 : 53.6
vvc_w_avg_8_16x4_c : 1486.3
vvc_w_avg_8_16x4_avx2 : 67.1
vvc_w_avg_8_16x8_c : 1907.8
vvc_w_avg_8_16x8_avx2 : 96.8
vvc_w_avg_8_16x16_c : 3883.6
vvc_w_avg_8_16x16_avx2 : 151.3
vvc_w_avg_8_16x32_c : 7974.8
vvc_w_avg_8_16x32_avx2 : 285.8
vvc_w_avg_8_16x64_c : 25160.6
vvc_w_avg_8_16x64_avx2 : 589.8
vvc_w_avg_8_16x128_c : 58328.1
vvc_w_avg_8_16x128_avx2 : 1169.8
vvc_w_avg_8_32x2_c : 1009.1
vvc_w_avg_8_32x2_avx2 : 65.6
vvc_w_avg_8_32x4_c : 2091.1
vvc_w_avg_8_32x4_avx2 : 96.8
vvc_w_avg_8_32x8_c : 3997.8
vvc_w_avg_8_32x8_avx2 : 156.3
vvc_w_avg_8_32x16_c : 8216.8
vvc_w_avg_8_32x16_avx2 : 269.6
vvc_w_avg_8_32x32_c : 21746.1
vvc_w_avg_8_32x32_avx2 : 635.3
vvc_w_avg_8_32x64_c : 31564.8
vvc_w_avg_8_32x64_avx2 : 1010.6
vvc_w_avg_8_32x128_c : 114373.3
vvc_w_avg_8_32x128_avx2 : 2013.6
vvc_w_avg_8_64x2_c : 2067.3
vvc_w_avg_8_64x2_avx2 : 97.6
vvc_w_avg_8_64x4_c : 3901.1
vvc_w_avg_8_64x4_avx2 : 154.8
vvc_w_avg_8_64x8_c : 7911.6
vvc_w_avg_8_64x8_avx2 : 268.8
vvc_w_avg_8_64x16_c : 16508.8
vvc_w_avg_8_64x16_avx2 : 501.8
vvc_w_avg_8_64x32_c : 38770.3
vvc_w_avg_8_64x32_avx2 : 1287.6
vvc_w_avg_8_64x64_c : 110350.6
vvc_w_avg_8_64x64_avx2 : 1890.8
vvc_w_avg_8_64x128_c : 141354.6
vvc_w_avg_8_64x128_avx2 : 3839.6
vvc_w_avg_8_128x2_c : 7012.1
vvc_w_avg_8_128x2_avx2 : 159.3
vvc_w_avg_8_128x4_c : 8146.8
vvc_w_avg_8_128x4_avx2 : 272.6
vvc_w_avg_8_128x8_c : 24596.8
vvc_w_avg_8_128x8_avx2 : 501.1
vvc_w_avg_8_128x16_c : 35918.1
vvc_w_avg_8_128x16_avx2 : 948.8
vvc_w_avg_8_128x32_c : 68799.6
vvc_w_avg_8_128x32_avx2 : 1963.1
vvc_w_avg_8_128x64_c : 133862.1
vvc_w_avg_8_128x64_avx2 : 3833.6
vvc_w_avg_8_128x128_c : 348427.8
vvc_w_avg_8_128x128_avx2 : 7682.8
vvc_w_avg_10_2x2_c : 118.6
vvc_w_avg_10_2x2_avx2 : 73.1
vvc_w_avg_10_2x4_c : 189.1
vvc_w_avg_10_2x4_avx2 : 89.3
vvc_w_avg_10_2x8_c : 382.8
vvc_w_avg_10_2x8_avx2 : 179.8
vvc_w_avg_10_2x16_c : 658.3
vvc_w_avg_10_2x16_avx2 : 185.1
vvc_w_avg_10_2x32_c : 1409.3
vvc_w_avg_10_2x32_avx2 : 290.8
vvc_w_avg_10_2x64_c : 2906.8
vvc_w_avg_10_2x64_avx2 : 793.1
vvc_w_avg_10_2x128_c : 6292.6
vvc_w_avg_10_2x128_avx2 : 1696.8
vvc_w_avg_10_4x2_c : 178.8
vvc_w_avg_10_4x2_avx2 : 80.1
vvc_w_avg_10_4x4_c : 581.6
vvc_w_avg_10_4x4_avx2 : 97.6
vvc_w_avg_10_4x8_c : 693.3
vvc_w_avg_10_4x8_avx2 : 128.1
vvc_w_avg_10_4x16_c : 1436.6
vvc_w_avg_10_4x16_avx2 : 179.8
vvc_w_avg_10_4x32_c : 2409.1
vvc_w_avg_10_4x32_avx2 : 292.3
vvc_w_avg_10_4x64_c : 4925.3
vvc_w_avg_10_4x64_avx2 : 746.1
vvc_w_avg_10_4x128_c : 10664.6
vvc_w_avg_10_4x128_avx2 : 1647.6
vvc_w_avg_10_8x2_c : 359.3
vvc_w_avg_10_8x2_avx2 : 80.1
vvc_w_avg_10_8x4_c : 925.6
vvc_w_avg_10_8x4_avx2 : 97.6
vvc_w_avg_10_8x8_c : 1360.6
vvc_w_avg_10_8x8_avx2 : 121.8
vvc_w_avg_10_8x16_c : 3490.3
vvc_w_avg_10_8x16_avx2 : 203.3
vvc_w_avg_10_8x32_c : 5266.1
vvc_w_avg_10_8x32_avx2 : 325.8
vvc_w_avg_10_8x64_c : 11127.1
vvc_w_avg_10_8x64_avx2 : 747.8
vvc_w_avg_10_8x128_c : 31058.3
vvc_w_avg_10_8x128_avx2 : 1424.6
vvc_w_avg_10_16x2_c : 624.8
vvc_w_avg_10_16x2_avx2 : 84.6
vvc_w_avg_10_16x4_c : 1389.6
vvc_w_avg_10_16x4_avx2 : 109.1
vvc_w_avg_10_16x8_c : 2688.3
vvc_w_avg_10_16x8_avx2 : 137.1
vvc_w_avg_10_16x16_c : 5387.1
vvc_w_avg_10_16x16_avx2 : 224.6
vvc_w_avg_10_16x32_c : 10776.3
vvc_w_avg_10_16x32_avx2 : 312.1
vvc_w_avg_10_16x64_c : 18069.1
vvc_w_avg_10_16x64_avx2 : 858.6
vvc_w_avg_10_16x128_c : 43460.3
vvc_w_avg_10_16x128_avx2 : 1411.6
vvc_w_avg_10_32x2_c : 1232.8
vvc_w_avg_10_32x2_avx2 : 99.1
vvc_w_avg_10_32x4_c : 4017.6
vvc_w_avg_10_32x4_avx2 : 134.1
vvc_w_avg_10_32x8_c : 9306.3
vvc_w_avg_10_32x8_avx2 : 208.1
vvc_w_avg_10_32x16_c : 8424.6
vvc_w_avg_10_32x16_avx2 : 349.3
vvc_w_avg_10_32x32_c : 20787.8
vvc_w_avg_10_32x32_avx2 : 655.3
vvc_w_avg_10_32x64_c : 40972.1
vvc_w_avg_10_32x64_avx2 : 904.8
vvc_w_avg_10_32x128_c : 85670.3
vvc_w_avg_10_32x128_avx2 : 1751.6
vvc_w_avg_10_64x2_c : 2454.1
vvc_w_avg_10_64x2_avx2 : 132.6
vvc_w_avg_10_64x4_c : 5012.6
vvc_w_avg_10_64x4_avx2 : 215.6
vvc_w_avg_10_64x8_c : 10811.3
vvc_w_avg_10_64x8_avx2 : 361.1
vvc_w_avg_10_64x16_c : 33349.1
vvc_w_avg_10_64x16_avx2 : 904.1
vvc_w_avg_10_64x32_c : 41892.3
vvc_w_avg_10_64x32_avx2 : 1220.6
vvc_w_avg_10_64x64_c : 66983.3
vvc_w_avg_10_64x64_avx2 : 2622.1
vvc_w_avg_10_64x128_c : 246508.8
vvc_w_avg_10_64x128_avx2 : 3316.8
vvc_w_avg_10_128x2_c : 7791.6
vvc_w_avg_10_128x2_avx2 : 198.8
vvc_w_avg_10_128x4_c : 10534.3
vvc_w_avg_10_128x4_avx2 : 337.3
vvc_w_avg_10_128x8_c : 21142.3
vvc_w_avg_10_128x8_avx2 : 614.8
vvc_w_avg_10_128x16_c : 40968.6
vvc_w_avg_10_128x16_avx2 : 1160.6
vvc_w_avg_10_128x32_c : 113043.3
vvc_w_avg_10_128x32_avx2 : 1644.6
vvc_w_avg_10_128x64_c : 230658.3
vvc_w_avg_10_128x64_avx2 : 5065.3
vvc_w_avg_10_128x128_c : 335236.3
vvc_w_avg_10_128x128_avx2 : 6450.3
vvc_w_avg_12_2x2_c : 185.3
vvc_w_avg_12_2x2_avx2 : 43.6
vvc_w_avg_12_2x4_c : 340.3
vvc_w_avg_12_2x4_avx2 : 55.8
vvc_w_avg_12_2x8_c : 632.3
vvc_w_avg_12_2x8_avx2 : 70.1
vvc_w_avg_12_2x16_c : 728.3
vvc_w_avg_12_2x16_avx2 : 108.1
vvc_w_avg_12_2x32_c : 1392.6
vvc_w_avg_12_2x32_avx2 : 176.8
vvc_w_avg_12_2x64_c : 2618.3
vvc_w_avg_12_2x64_avx2 : 757.3
vvc_w_avg_12_2x128_c : 6408.8
vvc_w_avg_12_2x128_avx2 : 1435.1
vvc_w_avg_12_4x2_c : 349.3
vvc_w_avg_12_4x2_avx2 : 44.3
vvc_w_avg_12_4x4_c : 607.1
vvc_w_avg_12_4x4_avx2 : 52.6
vvc_w_avg_12_4x8_c : 1134.8
vvc_w_avg_12_4x8_avx2 : 70.1
vvc_w_avg_12_4x16_c : 1378.1
vvc_w_avg_12_4x16_avx2 : 115.3
vvc_w_avg_12_4x32_c : 2599.3
vvc_w_avg_12_4x32_avx2 : 174.3
vvc_w_avg_12_4x64_c : 4474.8
vvc_w_avg_12_4x64_avx2 : 656.1
vvc_w_avg_12_4x128_c : 11319.6
vvc_w_avg_12_4x128_avx2 : 1373.1
vvc_w_avg_12_8x2_c : 595.8
vvc_w_avg_12_8x2_avx2 : 44.3
vvc_w_avg_12_8x4_c : 1164.3
vvc_w_avg_12_8x4_avx2 : 56.6
vvc_w_avg_12_8x8_c : 2019.6
vvc_w_avg_12_8x8_avx2 : 80.1
vvc_w_avg_12_8x16_c : 4071.6
vvc_w_avg_12_8x16_avx2 : 139.3
vvc_w_avg_12_8x32_c : 4485.1
vvc_w_avg_12_8x32_avx2 : 250.6
vvc_w_avg_12_8x64_c : 8404.8
vvc_w_avg_12_8x64_avx2 : 735.8
vvc_w_avg_12_8x128_c : 35679.8
vvc_w_avg_12_8x128_avx2 : 1252.6
vvc_w_avg_12_16x2_c : 1114.8
vvc_w_avg_12_16x2_avx2 : 46.6
vvc_w_avg_12_16x4_c : 2240.1
vvc_w_avg_12_16x4_avx2 : 62.6
vvc_w_avg_12_16x8_c : 13174.6
vvc_w_avg_12_16x8_avx2 : 88.6
vvc_w_avg_12_16x16_c : 5334.6
vvc_w_avg_12_16x16_avx2 : 144.3
vvc_w_avg_12_16x32_c : 8378.1
vvc_w_avg_12_16x32_avx2 : 234.6
vvc_w_avg_12_16x64_c : 21300.8
vvc_w_avg_12_16x64_avx2 : 761.8
vvc_w_avg_12_16x128_c : 32786.8
vvc_w_avg_12_16x128_avx2 : 1432.8
vvc_w_avg_12_32x2_c : 2154.3
vvc_w_avg_12_32x2_avx2 : 61.1
vvc_w_avg_12_32x4_c : 4299.8
vvc_w_avg_12_32x4_avx2 : 83.1
vvc_w_avg_12_32x8_c : 7964.8
vvc_w_avg_12_32x8_avx2 : 132.6
vvc_w_avg_12_32x16_c : 13321.6
vvc_w_avg_12_32x16_avx2 : 234.6
vvc_w_avg_12_32x32_c : 21149.3
vvc_w_avg_12_32x32_avx2 : 433.3
vvc_w_avg_12_32x64_c : 43666.6
vvc_w_avg_12_32x64_avx2 : 876.6
vvc_w_avg_12_32x128_c : 83189.8
vvc_w_avg_12_32x128_avx2 : 1756.6
vvc_w_avg_12_64x2_c : 3829.8
vvc_w_avg_12_64x2_avx2 : 83.1
vvc_w_avg_12_64x4_c : 8588.1
vvc_w_avg_12_64x4_avx2 : 127.1
vvc_w_avg_12_64x8_c : 17027.6
vvc_w_avg_12_64x8_avx2 : 310.6
vvc_w_avg_12_64x16_c : 29797.8
vvc_w_avg_12_64x16_avx2 : 415.6
vvc_w_avg_12_64x32_c : 43854.3
vvc_w_avg_12_64x32_avx2 : 773.3
vvc_w_avg_12_64x64_c : 137767.3
vvc_w_avg_12_64x64_avx2 : 1608.6
vvc_w_avg_12_64x128_c : 316428.3
vvc_w_avg_12_64x128_avx2 : 3249.8
vvc_w_avg_12_128x2_c : 8824.6
vvc_w_avg_12_128x2_avx2 : 130.3
vvc_w_avg_12_128x4_c : 17173.6
vvc_w_avg_12_128x4_avx2 : 219.3
vvc_w_avg_12_128x8_c : 21997.8
vvc_w_avg_12_128x8_avx2 : 397.3
vvc_w_avg_12_128x16_c : 43553.8
vvc_w_avg_12_128x16_avx2 : 790.1
vvc_w_avg_12_128x32_c : 89792.1
vvc_w_avg_12_128x32_avx2 : 1497.6
vvc_w_avg_12_128x64_c : 226573.3
vvc_w_avg_12_128x64_avx2 : 3153.1
vvc_w_avg_12_128x128_c : 332090.1
vvc_w_avg_12_128x128_avx2 : 6499.6Signed-off-by : Wu Jianhua <toqsxw@outlook.com>
-
libFLAC/cpu.c : Simplify OS SSE support detection.
28 juillet 2014, par Erik de Castro LopolibFLAC/cpu.c : Simplify OS SSE support detection.
Simplify the code that tries to detect whether OS supports SSE instructions.
a) Linux : "old" vs "new" sigaction
OBSOLETE_SIGCONTEXT_FLAVOR was disabled in Mar 2007 in commit 1ca3a445f.
According to <http://unixhelp.ed.ac.uk/CGI/man-cgi?sigaction>: "Support for
SA_SIGINFO was added in Linux 2.2" (released in Jan 1999). If noone wants to
use FLAC with Linux kernel 2.0 then it’s safe to delete this code.b) MSVC : try/catch vs. sigill_handler
TRY_CATCH_FLAVOR was enabled in Jan 2009 in commit a832ef32. According to the
comment in cpu.c, "sigill_handler flavor resulted in several crash reports on
win32". Also this sigill_handler flavor is not thread-safe.c) MinGW : fxsave/fxrestore vs. sigill_handler
The code was added Mar 2014 in commit 99d5154f. It’s better to use FXSR flavor
instead of sigill_handler flavor. The reasons are the same as for MSVC.Patch-from : lvqcl <lvqcl.mail@gmail.com>
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