Third-party support matrix#

Applies to Linux

2024-02-08

3 min read time

ROCm™ supports various third-party libraries and frameworks. We’ve tested our supported versions, so you can be assured that they work. Non-supported third-party versions may also work, but we haven’t tested these for functionality.

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, 2.1

5.7.x

1.12.1, 1.13, 2.0

2.12, 2.13

6.0.x

1.13, 2.0, 2.1

2.12, 2.13, 2.14

Communication libraries#

ROCm supports OpenUCX, 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 (UCC) library 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

6.0.x

2.0.1

22.9

For the latest documentation of these libraries, refer to the ROCm API libraries.