| // | |
| // Basic instrumentation profiler by Cherno | |
| // Usage: include this header file somewhere in your code (eg. precompiled header), and then use like: | |
| // | |
| // Instrumentor::Get().BeginSession("Session Name"); // Begin session | |
| // { | |
| // InstrumentationTimer timer("Profiled Scope Name"); // Place code like this in scopes you'd like to include in profiling | |
| // // Code | |
| // } |
This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).
Matrix multiplication is a mathematical operation that defines the product of
| # See /boot/overlays/README for all available options | |
| ############################################################################## | |
| ## Raspberry Pi Configuration Settings | |
| ## | |
| ## Revision 18, 2018/03/05 | |
| ## | |
| ## Details taken from the eLinux wiki | |
| ## For up-to-date information please refer to wiki page. | |
| ## | |
| ## Wiki Location : http://elinux.org/RPiconfig |
| from __future__ import print_function | |
| import picamera | |
| from picamera import mmal, mmalobj, exc | |
| from picamera.mmalobj import to_rational | |
| import time | |
| MMAL_PARAMETER_ANALOG_GAIN = mmal.MMAL_PARAMETER_GROUP_CAMERA + 0x59 | |
| MMAL_PARAMETER_DIGITAL_GAIN = mmal.MMAL_PARAMETER_GROUP_CAMERA + 0x5A |
This explains how to setup for GitHub projects which automatically generates Doxygen code documentation and publishes the documentation to the gh-pages branch using Travis CI.
This way only the source files need to be pushed to GitHub and the gh-pages branch is automatically updated with the generated Doxygen documentation.
Get an account at Travis CI. Turn on Travis for your repository in question, using the Travis control panel.
To create a clean gh-pages branch, with no commit history, from the master branch enter the code below in the Git Shell. This will create a gh-pages branch with one file, the README.md in it. It doesn't really matter what file is uploaded in it since it will be overwritten when the automatically generated documentation is published to th
| # -*- coding: utf-8 -*- | |
| """ | |
| This example is identical to https://gist.github.com/Overdrivr/efea3d363556c0dcf4b6 | |
| Except that here the plot is contained in a class. | |
| The superplot.start method starts the graph and returns a standard multiprocessing.queue | |
| the io function puts data in this queue, while the graph empties it regularly | |
| The outcome is : | |
| - a super fast application thanks to PyQtGraph | |
| - a main process that is never blocked by the graph | |
| Enjoy ! |
| import PIL.Image | |
| from cStringIO import StringIO | |
| import IPython.display | |
| import numpy as np | |
| def showarray(a, fmt='png'): | |
| a = np.uint8(a) | |
| f = StringIO() | |
| PIL.Image.fromarray(a).save(f, fmt) | |
| IPython.display.display(IPython.display.Image(data=f.getvalue())) |
| /* | |
| AnalogReadSerial | |
| Reads an analog input on pin 0, prints the result to the serial monitor. | |
| Attach the center pin of a potentiometer to pin A0, and the outside pins to +5V and ground. | |
| This example code is in the public domain. | |
| Upload this to the Arduino using the Arduino IDE! | |
| */ |
| DISPLAY=:0 cvlc -vvv --no-audio screen:// --screen-fps 1 --sout "#transcode{vcodec=MJPG,vb=800}:standard{access=http,mux=mpjpeg,dst=:18223/}" --sout-http-mime="multipart/x-mixed-replace;boundary=--7b3cc56e5f51db803f790dad720ed50a" |
