tinyML Talks: State of Hardware & Software Ecosystem for Low-Power ML Applications on RISC-V
Bilal Zafar
Co-founder and CEO
10xEngineers.ai
Muhammad Kamran
Compiler Engineer
10xEngineers.ai
RISC-V is an open, free, modular & extensible Instruction Set Architecture (ISA) enabling a new era of processor innovation through open standard collaboration. Many implementations have been developed lately by open-source communities and IP vendors, each using different microarchitectures to support a set of standard instructions and, in some cases, custom instructions targeting specific workloads & use-cases. As an evolving standard, support for the RISC-V hardware in the software ecosystem (OS, libraries, toolchains) is patchy and often difficult to navigate.
In this talk, we will present the latest RISC-V ISA specifications and upcoming standard extensions. We will survey available open-source and proprietary commercial implementations (i.e., processor cores, SoC &
boards) suitable for low-power applications. We will also discuss current software support for RISC-V and highlight some of the gaps.
Finally, we will present opportunities for open-source contributors to help accelerate the growth and adoption of RISC-V
Видео tinyML Talks: State of Hardware & Software Ecosystem for Low-Power ML Applications on RISC-V канала The tinyML Foundation
Co-founder and CEO
10xEngineers.ai
Muhammad Kamran
Compiler Engineer
10xEngineers.ai
RISC-V is an open, free, modular & extensible Instruction Set Architecture (ISA) enabling a new era of processor innovation through open standard collaboration. Many implementations have been developed lately by open-source communities and IP vendors, each using different microarchitectures to support a set of standard instructions and, in some cases, custom instructions targeting specific workloads & use-cases. As an evolving standard, support for the RISC-V hardware in the software ecosystem (OS, libraries, toolchains) is patchy and often difficult to navigate.
In this talk, we will present the latest RISC-V ISA specifications and upcoming standard extensions. We will survey available open-source and proprietary commercial implementations (i.e., processor cores, SoC &
boards) suitable for low-power applications. We will also discuss current software support for RISC-V and highlight some of the gaps.
Finally, we will present opportunities for open-source contributors to help accelerate the growth and adoption of RISC-V
Видео tinyML Talks: State of Hardware & Software Ecosystem for Low-Power ML Applications on RISC-V канала The tinyML Foundation
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
tinyML Talks Taiwan in Mandarin and English: Discovering tinyMLtinyML Summit 2022: Sensing Applications as a Driver for TinyML SolutionstinyML Neuromorphic Engineering Forum - Sensors SessiontinyML Vision Challenge - Himax & Edge ImpulsetinyML Talks Chao Xu: Enabling Neural network at the low power edge: A neural network compiler...SensMACH 2020 Daniel Situnayake: Embedded machine learning in the real worldtinyML Talks: Empowering the Edge: Practical Applications of Embedded Machine Learning on MCUstinyML Talks: Efficient AI for Wildlife ConservationtinyML Research Symposium 2022: Towards Agile Design of Neural Processing Units with ChiseltinyML Talks Phoenix: Novel Device and Materials in Emerging Memory for Neuromorphic ComputingtinyML Talks - Phoenix meetup: Analog TinyML for health management using intelligent wearablestinyML Talks India: Single Lead ECG Classification On Wearable and Implantable DevicestinyML Summit 2023:Personal Computing devices use-case and applications enabled by Smart SensorstinyML Talks: From the lab to the edge: Post-Training CompressiontinyML Talks: Meetup Italy with small-medium industriestinyML Hackathon Challenge 2023 - Infineon XENSIV 60GHz Radar Sensor and devkit explanationtinyML Auto ML Tutorial with QeexotinyML On Device Learning Forum - Warren Gross: On-Device Learning For Natural Language Processing..EMEA 2021 tiny Talks: Building Heterogeneous TinyML PipelinestinyML EMEA 2022- Eran Treister: Wavelet Feature Maps Compression for Image-to-Image CNNs