Leveraging the IBM z16 Integrated Accelerator for AI
Leveraging the IBM Integrated Accelerator for AI¶
The IBM Integrated Accelerator for AI is an on-chip AI accelerator available on the IBM Telum chip that is part of IBM z16. It is designed to enable high throughput, low latency inference for deep learning and machine learning.
With IBM z16 and the Integrated Accelerator for AI, you can build and train your models on any platform - including IBM zSystems and LinuxONE. When you are ready to deploy your assets, they will receive transparent acceleration and optimization on IBM zSystems, and will leverage the best available acceleration for the model type.
The IBM Integrated Accelerator for AI is more than just a matrix multiply accelerator - it provides optimization and acceleration for a set of complex functions commonly found in deep learning and machine learning models. This enables a broader set of functions to be accelerated on the chip.
As of IBM z16, the following operations are supported on the accelerator:
LSTM Activation GRU Activation Fused Matrix Multiply, Bias op Fused Matrix Multiply (w/ broadcast) Batch Normalization Fused Convolution, Bias Add, Relu Max Pool 2D Average Pool 2D Softmax Relu Tanh Sigmoid Add Subtract Multiply Divide Min Max Log
These allow the supporting frameworks to target an even broader set of operations to the Integrated Accelerator for AI.
Currently, the following frameworks can leverage the IBM z16 Integrated Accelerator for AI:
- ONNX deep learning models, when compiled using the IBM Deep Learning Compiler or ONNX-MLIR.
- Note that Pytorch, TensorFlow, Apache MXNet and other model types can be easily converted to ONNX.
- IBM Snap ML, a machine learning framework that provides optimized training and inference.
- Random Forest and Boosting Machine models are accelerated using the Integrated Accelerator for AI.
- IBM Snap ML provides:
- Seamless acceleration of sci-kit learn applications.
- Ability to execute lightGBM and XGBoost trained models when converted to JSON, PMML, or ONNX.
- TensorFlow (incubating)
- Available initially as an open beta in late 2Q 2022.
For further details, use the navigation bar on this page to select a 'Featured Frameworks and Technologies' choice.
Each of these are available as standalone packages, free of charge, or embedded within IBM products such as Watson Machine Learning for z/OS and Cloud Pak for Data.