What is Swift Performance AI?
- Swift AI is a high-performance AI and machine learning library written entirely in Swift that includes a set of common tools used for machine learning and artificial intelligence research.
- Easy to learn language incorpoated to provide many great attributes for development of all kinds.
- The artificial intelligence helps with our machine learning functionsDocumentation is clear and straightforward to follow, and there is a lot of support from the community
- Swift Performance AI is the most innovative WordPress Speed Up Plugin
- Swift Performance AI use innovative techniques to achive REAL speed improvment.
- Focusing on real user experience (field data), keep good content/code ratio and optimizing images in an SEO friendly way.
- Using Swift for numeric programming, such as training machine learning models, is not an area that many people are working on.
- There’s very little information around on the topic.
- But after a few weeks of research and experimentation I’ve managed to create a couple of libraries that can achieve the same speed as carefully optimized vectorized C code, whilst being concise and easy to use.
- In this article, I’ll take you through this journey and show you what I’ve learned about how to use Swift effectively for numeric programming.
- I will include examples mainly from my BaseMath library, hich provides generic math functions for
Double, and optimized versions for various collections of them.
- Swift is a general-purpose, multi-paradigm, compiled programming language.
- It was started by Chris Lattner while he was at Apple, and supported many concepts from Objective-C (the main language used for programming for Apple devices).
- Chris described the language to me as “syntax sugar for LLVM”, since it maps so closely to many of the ideas in that compiler framework.
- I’ve been coding for around 30 years, and in that time have used dozens of languages (and have even contributed to some.
- I always hope that when I start looking at a new language that there will be some mind-opening new ideas to find, and Swift definitely doesn’t disappoint.
- Swift tries to be expressive, flexible, concise, safe, easy to use, and fast.
- Most languages compromise significantly in at least one of these areas.
- Here’s my personal view of some languages that I’ve used and enjoyed, but all of which have limitations I’ve found frustrating at times.
- Python: Slow at runtime, poor support for parallel processing (but very easy to use)
- C, C++: hard to use (and C++ is slow at compile time), but fast and (for C++) expressive
- Julia: Poor support for general purpose programming, but fast and expressive for numeric programming. ( Edit: this may be a bit unfair to Julia; it’s come a long way since I’ve last looked at it!)
- Java: verbose (but getting better, particularly if you use Kotlin), less flexible (due to JVM issues), somewhat slow (but overall a language that has many useful application areas)
- C# and F#: perhaps the fewest compromises of any major programming language, but still requires installation of a runtime, limited flexibility due to garbage collection, and difficulties making code really fast (except on Windows, where you can interface via C++/CLI)
Remove Query Strings
Async Execute Combined JS
Defer JS, CDN Support
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Critical CSS On The Fly
Proxy 3rd Party JS
Inline Small Images
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- NVIDIA Deep Learning GPU Training System (DIGITS)
- Microsoft Cognitive Toolkit (Formerly CNTK)
- Google Cloud Deep Learning Containers
- AWS Deep Learning AMIs
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