HPC over Kubernetes

1. HKUBE
HPC over kubernetes

2. Agenda
About us
Overview
Architecture & Demonstration
Roadmap
Summary

3. 1/5
About us

4. The Core team
MAty Zissermam
(Team Leader & Software Developer )
Yehiyam livne
(Software Developer)
Nassi Harel
(Software Developer)
Tal Bahallol
(Software Developer)
Eli Maor
(Devops)
Eytan Godensky Ronen Kroitoro
(System Management)

5. 2/5
Overview

6. Hkube is an open source framework
that allows developers focus only on
writing algorithms.
We will do the rest…
Hkube for algorithms is like
Kubernetes to dockers

7. Legend
ALgorithm
BatchPipeline
Worker

8. Bare
Kubernetes
HKube
Core Modules
Algorithms
Pipelines
Hkube in layers

9. Main Concepts
Optimize Hardware
utilization
Language AgnosticDistributed pipeline of
algorithms
Algorithm monitoring Simple APISemi Automatic Jobs
Prioritization

10. Legend
Algorithm A
written in python
Algorithm B
written in c++
Algorithm C
written in R
Algorithm D
written in Python
Pipeline 1
Client
1
2
5
Pipeline 3
CPU 368
3
1150
After some time
Pipeline 2
. . .
What we try to solve
/500
2 X
4 X
7 X
7 X
4
3
5
1
2

11. It’s SimpleDeploy algorithm
Dockerize the
algorithm
Use CLI to add
the algorithm
to hkube
Implement a
simple
websocket api
for hkube
Run the
pipeline with
input
Register
webhooks for
result and
status
Create/store
pipeline
Run pipeline

12. User Instructions
Me
2. Split your problem to small pieces
input Classification
Me
Me Aggregation
3. Run it on Hkube
Dockerize Create Pipeline Descriptor Deploy & Run Make your boss happy
Took too long
1. ProblemInput Result
Face Detection & Cropping
find myself in a picture
X8

13. API
1.Create Descriptor 2.Run with Inputs

14. 3/5
Architecture &
Demonstration

15. Core Modules
Api Server
- Pipeline validation
- Client Api for status
result
- Notifies via webhooks
on data changes
Pipeline Driver
- Build DAG graph based
on Pipeline descriptor
schema
- Manage the pipeline
flow
Resource Manager & Executor
- Fetch hardware and
application data
- Calculate algorithm pod
count
- Create pods
Worker
- Runs algorithm container as
a sidecar
- Functions as a bridge for
communicating between
algorithm and hkube
Queues
- Implements heuristic for
prioritizing algorithm
tasks
- Handle algorithm task
execution

16. Algorithm Queue
face detection
Resource Executer
Algorithm Queue
classification
Resource
Manager
Pipeline Driver
Queue
Api Server
Algorithm Queue
Reduce-images positions
Worker
Algorithm
Classification
Architecture
X 100
Generate Job Yaml
For each pod
Get resource data
Pipeline Driver
Instance
Legend
Worker
Algorithm
reduce-images-positions
After algorithm ends.
wait for timeout and
then finish k8s job
Worker
Algorithm
face detection
Client
Run K8s Job

17. 4/5
Current Status & Roadmap

18. Version 1.0 (8/18)
- Dynamic allocation
- Extend algorithm monitoring metrics
- Extend hkube cli for supporting custom storage
- Well documented landing page
- Long lasting worker
- Triggering
Roadmap

19. Roadmap
Future
- Additional adapter for common orchestrators (spark&kubeflow)
- Worker affinity (GPU, specific node)
- Code API
- Cashing for algorithms (manually/input with hash )
- Cluster scaling
- Streaming Pipelines
- Sub-pipeline: for conditional execution
- Resource allocation heuristic improvements (ML)
- Hkube Dashboard
- More built in storage support
- Public algorithm store (helm like)
- PAAS
- Developer IDE - allow for easy developing and debugging of algorithms
- Authentication & Authorization
- Simplify API to HKUBE