This article will explore the classic division algorithms and how they can be implemented efficiently, in terms of code space and execution time, by exploiting machine features. Don’t expect anything astounding here, the algorithms are classic for a reason: this path is well-trodden.
This is the first in a series of articles that attempt to dispel the mystique around division algorithms. We do this by presenting coded algorithms that correctly divide, and describe how variations of these algorithms are used in emRun and emFloat, our C runtime and floating-point libraries.
In recent times, artificial intelligence (AI) and machine learning (ML) have become hot topics, enabling useful applications such as assistive and autonomous driving. Intelligent accessories in the home are now mainstream, employing adaptive audio and acoustic beamforming. This series of articles introduces what’s on the bench at SEGGER Labs…and coming soon.
My previous blog post covered the SEGGER Linker for RISC-V and the benefits provided by enhanced relaxation. This article continues to explore what SEGGER is doing with its linker technology, advancing what is typically possible.
One of the issues faced by RISC-V developers is that the code density of the RISC-V instruction set for deeply embedded processors does not match that of Cortex-M with existing tools. That is changing with the product innovations SEGGER have developed, such as the recently-announced SEGGER Linker, capable of reducing code size by up to […]
This posting continues to explore the performance of floating point and how microcontrollers can efficiently execute basic floating-point operations.
What makes a great runtime library different from a run-of-the-mill runtime library? This article will answer some of those questions with hard data and technical insights.
This article covers how SEGGER vastly improved its documentation process by taking control of the tools we use and, in the process, removed reliance on FrameMaker.
This continues the journey of analysing how the Akai Fire is controlled over MIDI and deals with the OLED display.
This continues the journey of reverse engineering how the Fire is controlled over MIDI and deals with illuminating the buttons and pads.