platform/upstream/caffeonacl - Domain: Machine Learning / ML Framework; Licenses: BSD-2-Clause;

Age	Commit message (Collapse)	Author	Files	Lines
2015-08-09	Multi-GPU	Cyprien Noel	1	-0/+1
	- Parallelize batches among GPUs and tree-reduce the gradients - The effective batch size scales with the number of devices - Batch size is multiplied by the number of devices - Split batches between GPUs, and tree-reduce the gradients - Detect machine topology (twin-GPU boards, P2P connectivity) - Track device in syncedmem (thanks @thatguymike) - Insert a callback in the solver for minimal code change - Accept list for gpu flag of caffe tool, e.g. '-gpu 0,1' or '-gpu all'. Run on default GPU if no ID given. - Add multi-GPU solver test - Deterministic architecture for reproducible runs
2014-10-02	add factory header to caffe hpp	Yangqing Jia	1	-0/+1

2014-08-06	LICENSE governs the whole project so strip file headers	Evan Shelhamer	1	-1/+0

2014-07-25	include benchmark.hpp	Yangqing Jia	1	-3/+3

2014-03-27	Standardize copyright, add root-level CONTRIBUTORS credit	Evan Shelhamer	1	-1/+1

2013-11-21	remove remaining distributed solver stuff	Yangqing Jia	1	-1/+0

2013-11-06	working asynchronous sgd code. may have errors.	Yangqing Jia	1	-0/+1

2013-10-17	cleaning codes	Yangqing Jia	1	-0/+4

2013-10-15	Reorganization of codes.	Yangqing Jia	1	-0/+15