2. Release overview

2.1. Operating system support

  • Ubuntu 18.04 is no longer supported.

  • PyTorch and TensorFlow 2 are no longer supported on CentOS 7.6.

  • The Poplar SDK for RHEL 8 requires the Python version to be upgraded to 3.9.

These changes enable the Poplar SDK to support PyTorch version 1.13.

2.2. PopTorch

Compatible with PyTorch 1.13 (upgraded from 1.10)

  • Added support for dict inputs.

  • Removed support for the legacy tracing frontend torch.jit.trace().

2.3. TensorFlow

TensorFlow 2.6.3

TensorFlow 1.15.5 (CentOS 7.6 only)

  • No significant changes.

2.4. Keras

Keras 2.6.0

  • Improved support for pipelining of nested Keras models.

  • Added automatic loss scaling support for training using Keras optimizers (experimental).

2.5. PopART

  • Added experimental support for custom transforms.

  • Improved handling of cached executables.

2.6. Poplar Libraries

  • Support sparse-dense and dense-sparse matrix multiplication where the sparsity structure of the sparse operand does not change.

  • Improved addConstant performance by 10x (and 20x when broadcasting) when adding large constants.

2.7. PopRun and PopDist

  • On IPU-Pods, automatically detect the RNIC interfaces to use for host-to-host communication.

2.8. PopEF

  • Added PopEF serialisation support for float8.

  • Added option to print tensor and feed data values and tensor shapes with popef_dump.

2.9. Model Runtime

  • Added user help and input verification to each of the tools.

  • Added functionality that allows NumPy arrays to be used with Model Runtime.

2.10. Poplar Triton Backend

  • Introduce new configuration option check_package_hash to prevent running an incompatible model.

2.11. Driver and utilities

  • Driver level support for C600 cards.

  • Command line tools support for C600 cards.