Birch: A Real-Time Multi-Domain Multi-Task Extended Reality Perception Accelerator

IF 2 Q3 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
IEEE Solid-State Circuits Letters Pub Date : 2026-01-01 Epub Date: 2026-03-12 DOI:10.1109/LSSC.2026.3673168
Kathleen Feng;Kai Bartolone;Kartik Prabhu;Brianna McColm;Xingyu Ni;Siddhant Gupta;Priyanka Raina
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引用次数: 0

Abstract

Birch is a system-on-chip (SoC) that efficiently and accurately accelerates the multi-task multi-domain extended reality (XR) perception pipeline, with workloads such as visual inertial odometry (VIO), eye gaze tracking, and scene understanding. Birch features vision modules with cascaded line buffers, in-step feature sorting, and double-buffered optical flow to extract and track quality features for VIO, a configurable matrix unit and vector unit for acceleration of deep neural network (DNN)-based tasks like eye gaze tracking and scene understanding, and reuse of the DNN vector unit for acceleration of matrix multiplications in VIO to save area in small-form-factor XR devices. Birch extracts and tracks features in 7.14 ms and 2.29 mJ/frame. For DNNs, Birch runs ResNet-18 at 109 frames/s and eye gaze extraction at 985 frames/s, $3.5\times $ and $1.6\times $ faster than prior work, respectively. ResNet-50 also runs in real time at 46.5 frames/s.
一个实时多领域多任务扩展现实感知加速器
Birch是一款片上系统(SoC),可高效、准确地加速多任务多域扩展现实(XR)感知管道,包括视觉惯性里程计(VIO)、眼球注视跟踪和场景理解等工作负载。Birch的特点是视觉模块具有级联线缓冲,步进特征排序和双缓冲光流,用于提取和跟踪VIO的质量特征,一个可配置的矩阵单元和向量单元,用于加速基于深度神经网络(DNN)的任务,如眼球跟踪和场景理解,并重用DNN向量单元加速VIO中的矩阵乘法,以节省小尺寸XR设备的面积。桦树提取和跟踪特征在7.14 ms和2.29 mJ/帧。对于dnn, Birch以109帧/秒的速度运行ResNet-18,以985帧/秒的速度运行眼睛凝视提取,分别比以前的工作快3.5倍和1.6倍。ResNet-50也以46.5帧/秒的速度实时运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Solid-State Circuits Letters
IEEE Solid-State Circuits Letters Engineering-Electrical and Electronic Engineering
CiteScore
4.30
自引率
3.70%
发文量
52
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