This is the Windows app named hls4ml whose latest release can be downloaded as iris1.3.0sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
hls4ml
DESCRIPTION:
hls4ml is an open-source framework that enables machine learning models to be implemented directly on hardware such as FPGAs and ASICs using high-level synthesis techniques. The system converts trained neural network models from common machine learning frameworks into hardware description code suitable for ultra-low-latency inference. This approach allows machine learning algorithms to run directly on specialized hardware, making them suitable for applications that require extremely fast response times and minimal power consumption. The framework was originally developed for high-energy physics experiments where real-time decision systems must process large volumes of data with strict latency constraints. Over time, it has expanded to support a variety of scientific and industrial applications including signal processing, embedded systems, and biomedical monitoring.
Features
- Conversion of machine learning models into FPGA-compatible hardware designs
- High-level synthesis workflow for implementing neural networks in hardware
- Ultra-low-latency inference suitable for real-time applications
- Support for models trained with frameworks such as Keras and TensorFlow
- Quantization and optimization tools for hardware-efficient deployment
- Applications in scientific computing, embedded systems, and signal processing
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/hls4ml.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.