Extending k8s API and Lesser known neural networks in Go

Slides from the talk I gave at Golang Taipei on 31st October, 2017

Transcript

1. K8S & LESSER KNOWN NEURAL NETWORKS IN GO GOLANG TAIPEI GATHERING #29
2. ABOUT ME ▸ Masters in Cybernetics, CTU, Prague ▸ Started Kubernetes London Meetup ▸ Containers: https://containerops.org/ ▸ Machine Learning: https://mlexplore.org/ ▸ Twitter: @milosgajdos ▸ Github: milosgajdos83
3. TONIGHT KUBERNETES LONDON MEETUP EXTENDING K8S WITH GO NEURAL NETWORKS IN GO QUIZ!
4. LET’S TALK ABOUT KUBERNETES LONDON
5. KUBERNETES LONDON MEETUP ▸ Started w/ Peter Idah (@peteridah) in Feb 2015 ▸ Currently almost 2k members ▸ Growing strong…still
7. LET’S TALK ABOUT KUBERNETES
8. KUBERNETES IN NUTSHELL ▸ Users interact with k8s [only] via API service ▸ Everything [useful] is an API object ▸ Users create them, Control Plane manages them ▸ Control Plane is a “Kernel”, APIs are “standard libs”
9. KUBERNETES IS THE POSIX OF THE CLOUD James Strachan, Redhat
10. EXTENDING KUBERNETES [API]
11. API SERVICE SHIPS AS A COMPILED BINARY
12. NEW K8S RELEASE SHIPS QUARTERLY
13. CONTRIBUTING TO K8S IS NOT EASY!
14. WHAT IF I TOLD YOU…ABOUT CDR?
15. CUSTOM RESOURCE DEFINITION (CRD) ▸ Extend k8s API with custom objects ▸ CDRs allow to use familiar UX: kubectl ▸ On their own just “dumb” storage of structured data ▸ Powerful in combination with CONTROLLERS
16. CDR EXAMPLE
17. CRD IN ACTION
18. CONTROLLERS GIVE YOU CDR SUPERPOWERS…SORT OF
19. CDR CONTROLLER IN ACTION
20. CONTROLLER REGISTRATION
21. CDR CONTROLLERS IN GO ▸ Easy to create, well…sort of :-) ▸ Sample controller:
 https://github.com/kubernetes/sample-controller ▸ Dig into the code deeper: 
 https://goo.gl/d12pQK ▸ Go even deeper: API aggregation ▸ Credit: James Munnelly (@JamesMunnelly )
22. LET’S TALK ABOUT NEURAL NETWORKS
23. WHY GO AND NEURAL NETWORKS ▸ Go is fun! Well, most of the time ;-) ▸ Statically typed language, memory safe ▸ Easy concurrency ▸ Reasonably fast [and still improving] runtime
24. PYTHON [R] + CUDA LEADING THE WAY
25. FPGA+GO=OK FOR SOME WORKLOADS
26. BUT STILL NOWHERE NEAR CUDA GPU MAGIC
27. YOU NEED A GOOD NUMERICAL LIBRARY
28. GO FOR NUMERICAL & SCIENTIFIC COMPUTING ▸ gonum: set of Go libraries for scientific computing
 https://www.gonum.org ▸ Numerical computations and optimization problems:
 https://github.com/gonum/gonum ▸ Particularly interesting packages:
 mat: matrix operations
 optimize: optimisation problems ▸ Plotting graphs:
 https://github.com/gonum/plot
29. CREATE MATRIX
30. BASIC MATRIX OPERATIONS
31. TRANSFORM MATRIX OPERATIONS
32. MATRIX VIEW OPERATIONS
33. STATISTICS, COMPARISONS ETC.
34. SOME NOTES ▸ The result of Matrix operation stored in receiver: ▸ Receiver must be initialized! ▸ Receiver get mutated by the operation! ▸ Panics when the indexes are out of bounds! ▸ Some operations return Vector, not Matrix! ▸ You can access raw backing data (float64 slices)
35. LESSER KNOWN NEURAL NETS…IN GO
36. SELF ORGANISING MAPS (SOM) ▸ Data clustering ▸ Unsupervised learning ▸ gosom: SOM implementation in Go
 https://github.com/milosgajdos83/gosom ▸ http://mlexplore.org/2017/01/13/ self-organizing-maps-in-go/
37. HOPFIELD NETWORKS ▸ Associative memory ▸ Supervised learning ▸ gopfield: Hopfield networks in Go
 https://github.com/milosgajdos83/gopfield ▸ http://mlexplore.org/2017/03/12/ hopfield-networks-in-go/
38. TIPS AND TRICKS ▸ Sometimes looping over a raw vector slice is faster than multiplying vectors using mat package functions
 AVOID UNNECESSARY ALLOCATIONS ▸ Avoid re-computing CPU “expensive” values (pow, exp…)
 CACHE AND RE-USE EXPENSIVE COMPUTATIONS ▸ Go Profiler is pretty awesome and it’s your best friend
 AVOID PREMATURE OPTIMISATIONS
39. SUMMARY ▸ Extending k8s API is simple and can give you super powers ▸ Neural Networks in Go are fun, but Python + CUDA still faster ▸ Stay awesome and keep hacking in Go!
40. REFERENCES ▸ Gist from this talk
 https://gist.github.com/milosgajdos83/ de311c901572644481d4b5dd3830d6cc ▸ Awesome list of Go for data science resources
 https://github.com/gopherdata/resources ▸ gorgonnia = Go + CUDA
 https://github.com/chewxy/gorgonia ▸ Go + FPGA
 https://github.com/ReconfigureIO