Metadata-Version: 2.1
Name: lowpy
Version: 0.1.3
Summary: High level GPU simulations of low level device characteristics in ML algorithms
Home-page: https://github.com/fordaj/lowpy
Author: Andrew Ford
Author-email: author@example.com
License: UNKNOWN
Description: # Welcome to LowPy (Pre-release)!
        <p align="center"><img src="logo.png" height="100px"></p>
        
        **LowPy** is a high level GPU simulator of low level device characteristics in machine algorithms. It seeks to streamline the investigation process when considering memristive and other novel devices for implementing a machine learning algorithm in hardware. By using the familiar [Keras](https://keras.io) syntax, it will be second nature to write GPU-optimized code to push your algorithm to its limits.
        
        # Features
        The aim is to focus first on the algorithms most published on in the field of neuromorphic computing, for both static and time series datasets.
        ### Datasets
        - MNIST
        ### Algorithms
        - Single Layer Perceptron (SLP)
        - Multi-Layer Perceprton (MLP)
        ### Activation Functions
        - Sigmoid
        ### Optimization Functions
        - Stochastic Gradient Descent (SGD)
        - SGD with Momentum
        ### Initialization Distributions
        - Uniform 
        - Normal
        ### Device Characteristics
        - Write Variability
        
        
        # Requirements
        The following are required to use LowPy:
        - GPU: NVIDIA
        - OS: Linux (should work on Windows, not tested)
        - Python 3.0 or newer
        - PyCUDA
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
