MIOpen v1.4.1

Notes:

• This release includes a bug fix for 3x3 convolutions
• Updated README file configuration instructions

Known Issues:

• RNNs do not support fp16
• Training with CNNs does not support fp16
• Users may encounter a warning that their performance database is out of date. The performance database can be updated by setting the environment variable for just the initial run of an application: MIOPEN_FIND_ENFORCE=search
  For more information on the performance database, see: https://rocmsoftwareplatform.github.io/MIOpen/doc/html/perfdatabase.html#

MIOpen v1.4.0

Notes:

• This release includes a number of performance improvements and bug fixes
• New features have been added to convolutions for auto-tuning kernels
• Activations now have new modes available
• Documentation has been updated and corrected

Changes:

• Fixed documentation errors
• Fixed bug in activations with pass-through mode
• Fixed performance database locking issues
• Fixed Winograd kernel behavior for stride 2 backwards data
• Fixed a bug in OpTensor layer
• Fixed a timing issue with batch normalization inline assembly
• Fixed issue with an unnecessary binary creation in assembly bug detection
• Fixed issue with disk program cache directory not being created
• Fixed a bug with convolution+bias
• Added to performance database functionality
• Added leaky-ReLU, clipped, and exponential-ReLU modes to activation
• Added documentation for performance database usage
• Added support for 1x1 convolutions with non-zero padding
• Added API for printing status codes as strings
• Added auto-tuning feature for convolutions
• Improved LSTM and GRU backwards pass performance
• Improved debug and error reporting information
• Improved performance of batch normalization spatial mode
• Improved find stage for convolutions
• Improved readability for user database file

Known Issues:

• RNNs do not support fp16
• Training with CNNs does not support fp16

MIOpen v1.3.0

Notes:

• Performance improvements for RNNs
• Performance improvements for convolutions using 1x1 filters
• Performance improvement for Batch Normalization
• This release adds preliminary fp16 support for Inference using CNNs
• Bug fixes for various components of MIOpen

Changes:

• Added 2 new API for RNNs: miopenGetRNNLayerParamOffset and miopenGetRNNLayerBiasOffset
• Added support for uninitialized hidden states and nullptr outputs in RNNs
• Added support for Set and Scale operations for strided tensors with dimensions 1 to 5
• Added multi-thread and multi-process support for the performance database
• Improved performance for OpTensor
• Fixed bug in convolutions for backward bias
• Fixed logic issues in get and set layer functions and related w_supertensor test
• Fixed hang in batch norm with batch sizes greater than 256

Known Issues:

• RNNs do not support fp16
• Training with CNNs does not support fp16

MIOpen v1.2.1

Notes:

This release adds support for ROCm 1.7.1.

MIOpen v1.2.0

Notes:

• This release adds the support for recurrent neural networks (RNNs) for three flavors - Vanilla, LSTMs, and GRU
• Users can now themselves update the perf-db file, which hosts the tuning parameters for convolutions, by setting appropriate environment variables

Changes:

• Over 50% improvement in ResNet performance since the last release
• Multiple padding modes like Same and Valid added
• Winograd convolution kernels added for strided bwd-data convolutions
• Tensor Ops allow for beta and alpha scaling values and support up to 5 dimensions with strides and offsets
• Tensor Copy supports up to 5 dimesnional copies with strides and offsets
• Unit-tests for LRN are added
• Several bug fixes for all the layers of the library

Known issues:

• RNNs may give incorrect result due to a known compiler bug; issue may particulary arise during some RNNs configs with GEMM of size power of 4
• Potential issue where OpenCL resources will be exhausted for large RNN

MIOpen v.1.1.4

Merge branch '1.1.x' of github.com:AMDComputeLibraries/MLOpen into 1.1.x

MIOpen v.1.1.1

• Performance improvements for the HIP backend
• Robust error-checking

MIOpen v1.1

Notes:

• The scaling parameter alpha and shift parameter beta for layers kernels are only supported for alpha = 1 and beta = 0. The exceptions to this are for miopenOptTensor, miopenConvolutionForwardBias, and miopenConvolutionBackwardBias.
• Currently, only 32-bit floats are supported in MIOpen.
• MIOpen only supports tensor layout NCHW.

Changes:

• Added persistent cache for compiled GPU kernels
• Performance improvements for batch normalization kernels
• Performance improvements for all types of convolutions for 1x1 filters
• Performance improvements for all types of convolutions with non-unit strides
• Performance improvements for backward-weights convolutions for 3x3 filters
• Performance improvements for the AddTensor operation
• Various bug fixes for Winograd convolutions

1.0.2

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