Third-party support matrix#
2024-03-22
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 |
||
|---|---|---|
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 |
1.11, 1.12.1, 1.13, 2.0 |
2.10, 2.11, 2.12 |
5.6.x |
1.12.1, 1.13, 2.0, 2.1 |
2.12, 2.13, 2.14 |
5.7.x |
1.12.1, 1.13, 2.0, 2.1 |
2.12, 2.13, 2.14 |
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.