Floating-point computations dominate the landscape of all AI/ML compute but also in automotive, avionics and healthcare. While performance and compute errors dominated the landscape of floating-point ...
The TMS320F28P550SJ from Texas Instruments is the industry's first real-time MCU with an integrated neural processing unit (NPU). It's designed to run convolutional-neural-network (CNN) models to help ...
Abstract: In this paper, we propose three modular multiplication algorithms that use only the IEEE 754 binary floating-point operations. Several previous studies have used floating-point operations to ...
Cleaning PV (photovoltaic) panels is essential for a PV station, as dirt or dust reduces the effective irradiation of solar energy and weakens the efficiency of converting solar energy into free ...
Why floating point is important for developing machine-learning models. What floating-point formats are used with machine learning? Over the last two decades, compute-intensive artificial-intelligence ...
pm-remez is a modern Rust implementation of the Parks-McClellan Remez exchange algorithm. It can be used as a Rust library and as a Python package via its Python bindings. pm-remez supports the design ...
The code to reproduce the results of the tests in [1] is available on GitHub. A different compiler can be used by setting the value of the variable compilerpath appropriately. If the chosen compiler ...
Abstract: In the emerging trend of Graphics Processing Architecture, IEEE 754-2008 Floating point numbers are being widely used. Convolution is one of the standard operations in image processing ...
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