Add 0.1.0rc3 changelog (#862) (#889)

* Add 0.1.0rc3 changelog



* Fix 0.1.0a0 changelog



* Update Changelog



* Apply suggestions from code review




* Update changelog with migration guide



* Add perf summary link



* Update CHANGELOG.md




---------

Signed-off-by: Charlie Truong <[email protected]>
Co-authored-by: Charlie Truong <[email protected]>

Author: ananthsub

CHANGELOG.md

@@ -1,5 +1,38 @@
 # Changelog
 
+## NVIDIA Megatron-Bridge 0.1.0rc3
+
+* Model Collection Support
+  * Llama
+  * Qwen 2, Qwen 3, Qwen 3 MoE
+  * DeepSeek
+  * Mamba
+* [Migration guide from NeMo 2 to Megatron-Bridge](https://docs.nvidia.com/nemo/megatron-bridge/0.1.0/nemo2-migration-guide.html)
+* [Contribution guide for adding a new model](https://docs.nvidia.com/nemo/megatron-bridge/0.1.0/adding-new-models.html)
+* [Checkpoint conversion from Hugging Face to Megatron](https://github.com/NVIDIA-NeMo/Megatron-Bridge/tree/main/src/megatron/bridge/models/conversion)
+* [Performance](https://docs.nvidia.com/nemo/megatron-bridge/0.1.0/performance-summary.html)
+  * MoE LLM
+    * Change the model to dropless with balanced gating
+    * Fusion of operators in router function
+    * Global permutation fusion with A2A dispatcher
+    * EP A2A communication overlap with computation in both 1F1B pipelining and non-pipelined training
+    * Precision-aware optimizer update to support BF16 states
+  * Megatron FSDP
+    * Migration from mcore FSDP to megatron FSDP
+    * Fusion of weight gradient copy to reduce-scatter communication buffer to WGRAD GEMM
+    * Removed redundant optimizer operations
+    * Use Zero1 (opt and master param sharding) in the replica domain of hybrid FSDP to further lower memory usage
+    * IB-SHARP support for the IB AllReduce of hybrid FSDP in a patch with NCCL2.28
+  * MXFP8
+    * Improved act grad all-gather overlap performance via userbuffer
+    * Parameter all-gather overlap with computation while the communication buffer sharing with reduce-scatter
+    * Fusion of MXFP8 scaling factor swizzling kernels
+    * Use PDL (Programmatic Dependent Launch) for quantization kernels to lower CPU overhead
+  * Others
+    * Full iteration cuda graph for dense model without pipelining
+    * Fusion of activation and cast fusion (currently tensor-wise scaling only)
+    * Store SwiGLU input in FP8 to save activation memory
+
 ## NVIDIA Megatron-Bridge 0.1.0a0
 
 * Llama and Qwen