Search Results for "squid-graph"

Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing large models to run within the constraints of mobile hardware. It supports a wide range of AI tasks including text generation, speech-to-text, vision processing, and retrieval-augmented workflows through a unified API interface. ...

...UI responsiveness guarantee is sometimes obligatory when running a model. Mechanism like automatically breaking OpenCL kernel into small units is introduced to allow better preemption for the UI rendering task. Graph level memory allocation optimization and buffer reuse are supported. The core library tries to keep minimum external dependencies to keep the library footprint small.

...Bender provides the ease of use of CoreML with the flexibility of a modern ML framework. Bender allows you to run trained models, you can use Tensorflow, Keras, Caffe, the choice is yours. Either freeze the graph or export the weights to files. You can import a frozen graph directly from supported platforms or re-define the network structure and load the weights. Either way, it just takes a few minutes. Bender suports the most common ML nodes and layers but it is also extensible so you can write your own custom functions. With Core ML, you can integrate trained machine learning models into your app, it supports Caffe and Keras 1.2.2+ at the moment. ...