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>> "A computation expressed using TensorFlow can be executed with little or no change on a wide variety of hetero- geneous systems, ranging from mobile devices
by nxzero 11y ago
>> "A computation expressed using TensorFlow can be executed with little or no change on a wide variety of hetero- geneous systems, ranging from mobile devices such as phones and tablets up to large-scale distributed systems of hundreds of machines and thousands of computational devices such as GPU cards."
Are there other comparable systems that deploy using the same build across all platforms?
If not, putting aside other advantages like doing computation across multiple machines, being able to using the same build is a major step forward in my opinion.
- mindcrime 11y agoAre there other comparable systems that deploy using the same build across all platforms? SystemML[1] doesn't, AFAIK, claim to scale down to mobile devices, but it does scale from a single desktop machine up to an arbitrarily large distributed cluster, using the same code. If you write code in DML or PyDML, the runtime will take care of distributing it across the cluster. And it's "smart" enough to take the cluster characteristics into account, and can also dynamically re-evaluate stages of the computation as the job is running, so it's always trying to use resources as efficiently as possible. [1]: https://systemml.apache.org/ https://systemml.apache.org/