The Cognitive Application Builder (CAB) is a project to develop a tool to improve programmer productivity when creating cognitive computing applications. In particular, to address the challenges of: - Data-driven development: many cognitive computing applications rely on large datasets, either during model training, or for model parameters. Managing this data during training and deployment is a key challenge.
- Heterogeneous execution: achieving high-performance on modern systems requires implementations for multicore CPU, GPU, FPGA, and other accelerators, and managing communication between these components.
- Application dataflow optimization: Allowing the developer to produce an intuitive description of the application, while providing compiler and runtime systems sufficient information to perrform static and dynamic optimizations.
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