Sr. Principal SOC Fabric Architect

Posted on 12/30/2022



201-500 employees

Develops AI/ML hardware accelerators and software

AI & Machine Learning

Senior, Expert

Toronto, ON, Canada

Required Skills
Data Structures & Algorithms
Data Analysis
  • Strong grasp of NoC topologies, routing algorithms, queuing, traffic scheduling, and QoS requirements
  • Expertise in cache coherency protocols (AMBA CHI/AXI protocol), DDR/LPDDR/GDDR memory technology, and IO technology (PCIe/CCIX/CXL)
  • Proficient in C/C++ programming. Experience in the development of highly efficient C/C++ CPU models
  • Collaborate with the software team and platform architecture team to understand fabric bandwidth and latency requirements and real-time constraints for AI accelerator, CPU, security, and networking traffic. Devise QoS and ordering rules among the CPU, accelerator, and IO coherent/non-coherent traffics
  • Identify representative traffic patterns for the software applications. Perform data-driven analysis to evaluate fabric topology, QoS, memory architecture , and u-architecture solutions to improve performance, power efficiency, or reduce hardware
  • Create directory-base cache coherency specification to satisfy performance requirements of coherent multiple-cluster CPU system and accelerator. Tradeoff protocol complexity and performance requirements
  • Design cache hierarchy to create best performance
  • Set SoC architecture direction based on the data analysis and work with a cross-functional team to achieve the best hardware/software solutions to meet PPA goals
  • Develop a SoC cycle-accurate performance model includes memory sub-systems, directory-based coherence cache controllers, fabric interconnects, and fabric switches that describe the microarchitecture, use it for evaluation of new features
  • Collaborate with RTL and Physical design engineers to make power, performance, and area trade-offs
  • Drive analysis and correlation of performance feature both pre and post-silicon
Desired Qualifications
  • Prior experience or strong understanding of traffic patterns for ML/AI algorithms in a heterogeneous computation system is a plus
  • Prior experience on formal verification of cache coherence protocols is a plus

Tenstorrent specializes in developing high-quality AI/ML accelerators, including individual PCIe cards, workstations, servers, and ultra-dense Galaxy pods, featuring industry-standard chiplets and a modular RISC-V CPU. Their products also incorporate a BUDA software framework designed for open-source collaboration, enabling efficient and scalable hardware for deep learning applications.

Company Stage

Series C

Total Funding



Toronto, Canada



Growth & Insights

6 month growth


1 year growth


2 year growth