ROCm/docs/about/compatibility/3rd_party_support_matrix.md

Third party support matrix

ROCm™ supports various 3rd party libraries and frameworks. Supported versions are tested and known to work. Non-supported versions of 3rd parties may also work, but aren't tested.

Deep Learning

ROCm releases support the most recent and two prior releases of PyTorch and TensorFlow

ROCm	PyTorch	TensorFlow	MAGMA
5.0.2	1.8, 1.9, 1.10	2.6, 2.7, 2.8
5.1.3	1.9, 1.10, 1.11	2.7, 2.8, 2.9
5.2.x	1.10, 1.11, 1.12	2.8, 2.9, 2.9
5.3.x	1.10.1, 1.11, 1.12.1, 1.13	2.8, 2.9, 2.10
5.4.x	1.10.1, 1.11, 1.12.1, 1.13	2.8, 2.9, 2.10, 2.11	2.5.4
5.5.x	1.10.1, 1.11, 1.12.1, 1.13	2.10, 2.11	2.5.4
5.6	1.11, 1.12.1, 1.13.1	2.12	2.5.4

(communication_libraries)=

Communication libraries

ROCm supports OpenUCX an "an open-source, production-grade communication framework for data-centric and high-performance applications".

UCX version	ROCm 5.4 and older	ROCm 5.5 and newer
-1.14.0	COMPATIBLE	INCOMPATIBLE
1.14.1+	COMPATIBLE	COMPATIBLE

The Unified Collective Communication Library UCC also has support for ROCm devices.

UCC version	ROCm 5.5 and older	ROCm 5.6 and newer
-1.1.0	COMPATIBLE	INCOMPATIBLE
1.2.0+	COMPATIBLE	COMPATIBLE

Algorithm libraries

ROCm releases provide algorithm libraries with interfaces compatible with contemporary CUDA / NVIDIA HPC SDK alternatives.

• Thrust → rocThrust
• CUB → hipCUB

ROCm	Thrust / CUB	HPC SDK
5.0.2	1.14	21.9
5.1.3	1.15	22.1
5.2.x	1.15	22.2, 22.3
5.3.x	1.16	22.7
5.4.x	1.16	22.9
5.5.x	1.17	22.9
5.6	1.17.2	22.9

For the latest documentation of these libraries, refer to the associated documentation.