Stream - Multi-core accelerator design space exploration with layer-fused scheduling
Project description
Stream
Stream is a HW architecture-mapping design space exploration (DSE) framework for multi-core deep learning accelerators. The mapping can be explored at different granularities, ranging from classical layer-by-layer processing to fine-grained layer-fused processing. Stream builds on top of the ZigZag DSE framework, found here.
More information with respect to the capabilities of Stream can be found in the following paper:
Documentation
Documentation for Stream is underway!
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
stream-dse-0.0.5.tar.gz
(76.6 kB
view hashes)
Built Distribution
stream_dse-0.0.5-py3-none-any.whl
(116.2 kB
view hashes)
Close
Hashes for stream_dse-0.0.5-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | bb293589a9a0be9cc44a402804e863989fbbc78808651863742c27dfef08b5b8 |
|
MD5 | 403de224ee268af28b6feb7148e77e66 |
|
BLAKE2b-256 | df173d519df916019fa131d2d87db586505a7cf0c40f4eb8c60e2aa7ed0580cb |