MathWorks’ MATLAB 2018b release serves up a number of new features, including the Deep Learning Toolbox that supports development of machine-learning applications. Other new features include the 5G ...
Today, I’ve teamed up with Ram Cherukuri of MathWorks to provide an overview of the MathWorks toolchain for machine learning (ML) and the deployment of embedded ML inference on Arm Cortex-A using the ...
Hardware and device makers are in a mad dash to create or acquire the perfect chip for performing deep learning training and inference. While we have yet to see anything that can handle both parts of ...
MOUNTAIN VIEW, Calif., May 31, 2017 — Flex Logix Technologies, Inc., a leading developer of embedded FPGA IP cores and software, today announced it has completed design of its second-generation ...
Over the last couple of years, the idea that the most efficient and high performance way to accelerate deep learning training and inference is with a custom ASIC—something designed to fit the specific ...
Previous sections have described the complementary strengths of CPUs, GPUs, and FPGAs for different types of deep learning operations. With the emergence of new use cases, there will be a growing ...
FPGAs or GPUs, that is the question. Since the popularity of using machine learning algorithms to extract and process the information from raw data, it has been a race between FPGA and GPU vendors to ...
Mipsology’s Zebra Deep Learning inference engine is designed to be fast, painless, and adaptable, outclassing CPU, GPU, and ASIC competitors. I recently attended the 2018 Xilinx Development Forum (XDF ...
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