open source project checked

pen source projects I scatched

To review how many open source projects I tried to study has been in my mind for a long time. I am always interested in new areas, new trends, and want to understand a little more, few contribution by now. One college friend, who worked at Intel China, first brought me to GTC 2008 at Beijing, where my eyes is opened first time, to know there is so many amazing works around the world.

1) HPC/FEA/CFD

after 2008, I was driven by computing mechanics more

HPCG: a benchmark work to test FLOPs, which I used as a class project at Buffalo

PETSC: a large sparse matrix solver, developed from Texas Austin, also met at Buffalo. the math is attracted me more and it is complex and a good learning material for C++

LibMesh: based on PETSC to do FEM. ran some demo and interested in math more

GPU-SPH: GPU implementd of SPH(CFD algorithm), during 2011, GPU is popular in applied mechanics.

PetIBM: immersed boundary method (CFD algorithm), used as a class project

OpenFEM, OpenFOAM etc. during that period, I collected many small/big open source CFD/FEA projects, but few study.

2) Game Engine

at 2011, Virtual Reality is attracting

CHAI3D: my friend show me a demo, but I didn’t go through

LiquidFun: google product

Box2D: for fun, like LiquidFun, where cmake, configure skills played

That time I also collected many other game engines from web, e.g. Unreal, skynet.. it’s so cool to be a game developer, but no time to deep in

3) Robot

at 2014, robot is hot

ROS: that’s my way to study the platform first, with a few study and no more

SLAM: the cool concept when to uderstand the core algorithm

OpenCV: used everywhere, read some docs, but not used independtely

Arduino: platform, when I joined the Detroit Hacking Night(DHN) meetup

RasiBerry: similar experience during DHN, later I tried to implement deep learning detection algorithm on a race car, not finished till now

RTOS: go through like 2-month ago, when I feel I need more understand at embedded system. simple to understand, but not sure how can I master in practice

4) Deep Learning

after 2016, DL is so popular, many frameworks, online courses, papers bursting, no way to keep calm.

TensorFlow: I thought it’s easy at first, but really didn’t go to the code, but implemented some examples

Caffe: the DL framework jumped in, first knew about Google protocol buffer, very confused at that time

ChatAI: I tried to add some fun in WeChat public platform

5) Vehicle

Buffalo Car simulator: at Buffalo lab, there was a physical car simulator, and code in OSG, cool project to learn C++

SimCar: later I had chance to know many open source/ commercial car simulators

AGL: at 2017, started to view AGL updates, try to keep in mind the new trends in vehicle software fields

GEVIVI: same time with AGL, interested in IVI as a sub-field

openXC, SmartDeviceLink: OEM level apps

6) Web & Mobile

at 2017, luckly transfered to a web project, have the chance to know AngularJS, Node.js and event driven, REST, AJAX, async, many new and exciting ideas here.

Hexo.io: a static blog engine

web crawler: looks like a hack skill

async event I/O lib: moduo, event.js

top github Rankers have js projects, looks very intersting

many little tools when playing with Linux, system level, apps. One big stuff is Linux Process Communication(IPC). I used share memory in one product but never had a chance to know the big picture of IPC, later want to know about Linux network, and see socket, signal… feel connected.

CMAKE:

QT:

Glib:

MKL: intel math kernal lib, cool in first impression

plugin-pattern in embedded software

the good is know diversity, the short I don’t have done any contribution to combine these experince

GBM