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Updated Release Notes for v0.102.
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ReleaseNotes.txt

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============================== (Pending) Release Notes: v1.00 ==============================
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Support for new training algorithms:
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Support for new network structures:
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Support for new layers:
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Python front-end:
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Performance optimizations:
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Model portability & usability:
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Experiments & Applications:
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Internal features:
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I/O & data readers:
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Build system:
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Bug fixes:
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Retired features:
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============================== Release Notes: v0.102 ==============================
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Support for new training algorithms:
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- LTFB is now a first-class training algorithm.
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- LTFB now allows multiple metrics. The local algorithm is favored by
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- Parallelize computation of Gaussian random numbers
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- Optimizing tessellate, concatenate, and slice layers on CPU
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Model portability & usability:
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Experiments & Applications:
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- Added experiment scripts for ATOM cWAE Gordon Bell simulations
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- LBANN-ATOM model inference and analysis

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