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3rd Party Support Matrix

3rd Party Support Matrix#

Applies to Linux and Windows

2023-10-13

5 min read time

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

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

5.5.x

1.10.1, 1.11, 1.12.1, 1.13

2.10, 2.11, 2.13

5.6.x

1.12.1, 1.13, 2.0

2.12, 2.13

5.7.x

1.12.1, 1.13, 2.0

2.12, 2.13

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.x

1.17.2

22.9

5.7.x

1.17.2

22.9

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