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Making the Dead Rise, and Other Impossible Tasks

My current job is to lead our company's work on dynamic server languages, such as performance optimization and feature enabling. Besides PHP and HHVM, we want to improve Python. There is a huge amount of Python code in use out there, for example running OpenStack, Swift, DropBox and many others. What I didn't realize when I took the job was that much of this use is in a "dead" language.
Autor David S. (Blackbelt) Última actualización 15/10/2019 - 17:57
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The JITter Conundrum - Just in Time for Your Traffic Jam

In interpreted languages, it just takes longer to get stuff done - I earlier gave the example where the Python source code a = b + c would result in a BINARY_ADD byte code which takes 78 machine instructions to do the add, but it's a single native ADD instruction if run in compiled language like C or C++. How can we speed this up? Or as the performance expert would say, how do I decrease...
Autor David S. (Blackbelt) Última actualización 15/10/2019 - 19:42
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Core Challenge In Speeding Up Python, PHP, HHVM, Node.js...

A traditional compiler translates a high-level computer program into machine code for the CPU you want to run it on. An interpreted language translates a high-level language into the machine code for some imaginary CPU. For historical reasons, this imaginary CPU is called a "virtual machine" and its instructions are called "byte code." One advantage of this approach is development speed: creating...
Autor David S. (Blackbelt) Última actualización 15/10/2019 - 19:43
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Dynamic Languages Take Over the Internet

The server world has really embraced Python in a big way. For example, the OpenStack project is a very popular Infrastructure as a Service offering, and most of it is written in Python. This makes Python a leader for Software Defined Infrastructure (SDI), Software Defined Storage (SDS) and Software Defined Networking (SDN).
Autor David S. (Blackbelt) Última actualización 15/10/2019 - 19:44