- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
The Intel® Data Analytics Acceleration Library (Intel® DAAL) is designed to help software developers reduce the time it takes to develop their applications and provide them with improved performance. Intel DAAL helps applications make better predictions faster and analyze larger data sets with the available compute resources at hand. The library is updated to take advantage of next generation processors even before they're available.
What's New in Intel® DAAL 2017 Update 1
- Added K-Nearest Neighbors (KNN) algorithm for batch computing mode
- Added distributed processing mode for neural network training to support distributed parallel data processing
- Introduced diagonal variance-covariance matrices in EM GMM and controls to treat degenerated covariance matrices
- Introduced k-means++ and k-means|| initialization methods for K-Means clustering
- Introduced the Gaussian initializer for neural network model parameters (weights and biases) initialization
- Introduced min-max normalization algorithm
- Added multiple ground truth tensors and multiple result tensors for neural networks training and inference stage, respectively
- Added optional arguments and results in the SGD solver to enable computation resumption from a paused state
- Added support for merging of the numeric tables by rows
- Added support for symmetric and triangular packed numeric tables in Java
- Performance improvements for the following functions:
- Neural network training and inference, including support for batch mode on the inference stage
- Local response normalization layer and 2D max pooling layer
- Abs and Tanh backward layers
- Cosine distance for result in lower triangular layout, correlation distance for result in full, lower- and upper triangular layouts
- Lower order moments
- z-score normalization
- PCA
- Kernel functions for CSR NumericTables
- CSV feature manager
- Bug fixes for the following components:
- Multi-class classifier
- IBFGS optimization solver
- Documentation
The open source Intel DAAL project is also updated accordingly.
Checkout Online Release notes for more information.
Link Copied
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Dear Zhang,
Can DAAL routines be called from Fortran? I'm a Fortran developer, and this would be superb for me.
Tx. in advance
Andras
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Andras, that's not possible for now. The current version support Java, C++ and Python API only.
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
This is sad. Are you considering to extend it to Fortran later on?
best regards
Andras
- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page