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simplify README #440

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Sep 9, 2019
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simplify README #440

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36 changes: 4 additions & 32 deletions README.md
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[![FOSSA Status](https://app.fossa.com/api/projects/git%2Bgh.neting.cc%2Fvolcano-sh%2Fvolcano.svg?type=shield)](https://app.fossa.com/projects/git%2Bgh.neting.cc%2Fvolcano-sh%2Fvolcano?ref=badge_shield) [![CII Best Practices](https://bestpractices.coreinfrastructure.org/projects/3012/badge)](https://bestpractices.coreinfrastructure.org/projects/3012)


Volcano is a batch system built on Kubernetes. It provides a suite of mechanisms currently missing from
Kubernetes that are commonly required by many classes of batch & elastic workload including:

1. machine learning/deep learning,
2. bioinformatics/genomics
3. other "big data" applications.

These types of applications typically run on generalized domain
frameworks like TensorFlow, Spark, PyTorch, MPI, etc, which Volcano integrates with.

Some examples of the mechanisms and features that Volcano adds to Kubernetes are:

1. Job management extensions and improvements, e.g:
1. Multi-pod jobs
2. Lifecycle management extensions including suspend/resume and
restart.
3. Improved error handling
4. Indexed jobs
5. Task dependencies
2. Scheduling extensions, e.g:
1. Co-scheduling
2. Fair-share scheduling
3. Queue scheduling
4. Preemption and reclaims
5. Reservations and backfills
6. Topology-based scheduling
3. Runtime extensions, e.g:
1. Support for specialized container runtimes like Singularity,
with GPU accelerator extensions and enhanced security features.
4. Other
1. Data locality awareness and intelligent scheduling
2. Optimizations for data throughput, round-trip latency, etc.
Volcano is a batch system built on Kubernetes. It provides a suite of mechanisms that are commonly required by
many classes of batch & elastic workload including: machine learning/deep learning, bioinformatics/genomics and
other "big data" applications. These types of applications typically run on generalized domain frameworks like
TensorFlow, Spark, PyTorch, MPI, etc, which Volcano integrates with.

Volcano builds upon a decade and a half of experience running a wide
variety of high performance workloads at scale using several systems
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