BookQt5's profile picture. A book about C++ and Qt-5 performance techniques by @mrkkrj, published in Jan. 2019: http://packtpub.com/application-de….

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@BookQt5

A book about C++ and Qt-5 performance techniques by @mrkkrj, published in Jan. 2019: http://packtpub.com/application-de….

Ghim

Some good reviews 🥳 here:

BookQt5's tweet image. Some good reviews 🥳 here:

We touched upon that in the book, but for the UI that's normally not that important. But if you are curious, here its is: branch prediction deep dive.

A detailed discussion of branch prediction and performance - because in that industry: "For low-latency systems, a branch miss rate over 1% should raise alarms, and sub-0.5% is ideal for ultra-low-latency paths." 😮 #cpp #cplusplus #performance johnfarrier.com/branch-predict…



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C++ Insights - Episode 57: More performance thanks to more implicit moves in C++20 In this episode, you learn about a change in the standard that can give you more performance, thanks to the implicit move. youtu.be/3CR1ow5BfJM #cppinsights #cpp

Andreas__Fertig's tweet card. C++ Insights - Episode 57: More performance thanks to more implicit...

youtube.com

YouTube

C++ Insights - Episode 57: More performance thanks to more implicit...


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The free PDF version is now available 🎉 github.com/dendibakh/perf…

📢 It's here! The second edition of my book "Performance Analysis and Tuning on Modern CPUs" is out NOW! Dive into low-level optimizations and learn to write fast code like a pro. Grab your copy: amzn.to/4fsroBs Please RT to spread the word! #NewBook #BookRelease 🧵1/3



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Come & get it!


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CPU vs FPGA - what an easy and well explanation in 25 seconds


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Redis is data structure store that can be used as a database, cache, and message broker. It is used by a wide range of major corporations. Recently, Redis has adopted our library (fast_float) and they report a substantial performance boost (30%).

lemire's tweet image. Redis is data structure store that can be used as a database, cache, and message broker. It is used by a wide range of major corporations. Recently, Redis has adopted our library (fast_float) and they report a substantial performance boost (30%).

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i_bogosavljevic's tweet image.

"Optimizing compilers may turn your conventional code into a table lookup. For example, a switch-case is sometimes compiled to a small table ... what appears like a branch (if-else) might be compiled to conditional move instructions or even to a table. - as discussed in the book


There are also some new text features like dynamic font support with variable axes (e.g. wght, wdth and ital in the image below). #Qt6_7 qt.io/blog/text-impr…

BookQt5's tweet image. There are also some new text features like dynamic font support with variable axes (e.g. wght, wdth and ital in the image below). #Qt6_7

qt.io/blog/text-impr…

Support for Google Protocol Buffers has been recently (Qt 6.7) added to Qt as QtGrpc module: 👍 doc.qt.io/qt-6/qtgrpc-in…


An allocator story in embedded context:

More of the musl+alpine story: the allocators (a long time favourites of mine, BTW...) -> "It is known that some memory allocation patterns lead to bad performance with the new hardened malloc. However, the security benefits ... to some extent justifies the performance costs"



"C++ templ library for high perf. SIMD based sorting routines for built-in integers, floats... and custom defined C++ objects... accelerated using AVX-512/AVX2 when available ... library auto picks the best version depending on the processor it is run on" github.com/intel/x86-simd…

github.com

GitHub - numpy/x86-simd-sort: C++ template library for high performance SIMD based sorting algori...

C++ template library for high performance SIMD based sorting algorithms - numpy/x86-simd-sort


"Toward the end of last year Intel quietly made available x86-simd-sort via their GitHub account. It's a C++ header file library for high performance SIMD sorting though in its current form is just focused on an AVX-512 quicksort implementation."


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Rolling your own fast matrix multiplication: loop order and vectorization If you must multiply matrices, you should use dedicated libraries. However, we sometimes need to roll our own code. In C++, you can quickly write your own Matrix template: How do you implement a matrix…

lemire's tweet image. Rolling your own fast matrix multiplication: loop order and vectorization

If you must multiply matrices, you should use dedicated libraries. However, we sometimes need to roll our own code. In C++, you can quickly write your own Matrix template:

How do you implement a matrix…
lemire's tweet image. Rolling your own fast matrix multiplication: loop order and vectorization

If you must multiply matrices, you should use dedicated libraries. However, we sometimes need to roll our own code. In C++, you can quickly write your own Matrix template:

How do you implement a matrix…
lemire's tweet image. Rolling your own fast matrix multiplication: loop order and vectorization

If you must multiply matrices, you should use dedicated libraries. However, we sometimes need to roll our own code. In C++, you can quickly write your own Matrix template:

How do you implement a matrix…
lemire's tweet image. Rolling your own fast matrix multiplication: loop order and vectorization

If you must multiply matrices, you should use dedicated libraries. However, we sometimes need to roll our own code. In C++, you can quickly write your own Matrix template:

How do you implement a matrix…

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Join Till Adam, CCO of @KDABQt, and Christoph Hennersperger, co-founder of Luma Vision, as they explore building advanced medical imaging solutions with Qt. Full presentation here: hubs.li/Q02B3W730 #Healthcare #MedTech #MedicalImaging #MedicalTechnology #MedicalDevice

qtproject's tweet image. Join Till Adam, CCO of @KDABQt, and Christoph Hennersperger, co-founder of Luma Vision, as they explore building advanced medical imaging solutions with Qt.

Full presentation here: hubs.li/Q02B3W730

#Healthcare #MedTech #MedicalImaging #MedicalTechnology #MedicalDevice

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If you have good performance oriented architecture design, you have less hot spots to optimize. If not, then you run into death by thousand cuts problem. After fixing a few critical issues, everything starts to look like a hotspot, so you have to rewrite everything.


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"And that explain why companies do full rewrites of their code for performance: the effort needed to squeeze more performance from the existing code becomes too much and a __complete rewrite is cheaper__."

Hotspot performance engineering fails: Developers often believe that software performance follows a Pareto distribution: 80% of the running time is spent in 20% of the code. Using this model, you can write most of your code without any care for performance and focus on the…



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