Internship

Compiler Software Engineer Intern

Posted on 11/13/2024

d-Matrix

d-Matrix

201-500 employees

AI compute platform for datacenters

Enterprise Software
AI & Machine Learning

Toronto, ON, Canada

Hybrid position requiring onsite work in Toronto for 3 days per week.

Category
Embedded Engineering
Software Engineering
Required Skills
Data Structures & Algorithms
C/C++
Requirements
  • Bachelor’s degree in computer science or equivalent 3 years towards an Engineering degree with emphasis on computing and mathematics coursework.
  • Proficiency with C++ object-oriented programming is essential.
  • Understanding of fixed point and floating-point number representations, floating point arithmetic, reduced precision floating point representations and sparse matrix storage representations and the methods used to convert between them.
  • Some experience in applied computer programming (e.g. prior internship).
  • Understanding of basic compiler concepts and methods used in creating compilers (ideally via a compiler course).
  • Data structures and algorithms for manipulating directed acyclic graphs.
  • Familiarity of sparse matrix storage representations.
  • Hands on experience with CNN, RNN, Transformer neural network architectures.
  • Experience with programming GPUs and specialized HW accelerator systems for deep neural networks.
  • Passionate about learning new compiler development methodologies like MLIR.
  • Enthusiastic about learning new concepts from compiler experts in the US and a willingness to defeat the time zone barriers to facilitate collaboration.
Responsibilities
  • design, implement and evaluate a method for managing floating point data types in the compiler.
  • work under the guidance of two members of the compiler backend team.
  • engage and collaborate with engineering team in the US to understand the mechanisms made available by the hardware design to perform efficient floating point operations using reduced precision floating point data types.
  • demonstrate successful completion of the project by a simple model output by the compiler incorporating the code that executes correctly on the hardware instruction set architecture (ISA) simulator.

d-Matrix focuses on improving the efficiency of AI computing for large datacenter customers. Its main product is the digital in-memory compute (DIMC) engine, which combines computing capabilities directly with programmable memory. This design helps reduce power consumption and enhances data processing speed while ensuring accuracy. d-Matrix differentiates itself from competitors by offering a modular and scalable approach, utilizing low-power chiplets that can be tailored for different applications. The company's goal is to provide high-performance, energy-efficient AI inference solutions to large-scale datacenter operators.

Company Stage

Series B

Total Funding

$149.8M

Headquarters

Santa Clara, California

Founded

2019

Growth & Insights
Headcount

6 month growth

2%

1 year growth

0%

2 year growth

9%
Simplify Jobs

Simplify's Take

What believers are saying

  • Growing demand for energy-efficient AI solutions boosts d-Matrix's low-power chiplets appeal.
  • Partnerships with companies like Microsoft could lead to strategic alliances.
  • Increasing adoption of modular AI hardware in data centers benefits d-Matrix's offerings.

What critics are saying

  • Competition from Nvidia, AMD, and Intel may pressure d-Matrix's market share.
  • Complex AI chip design could lead to delays or increased production costs.
  • Rapid AI innovation may render d-Matrix's technology obsolete if not updated.

What makes d-Matrix unique

  • d-Matrix's DIMC engine integrates compute into memory, enhancing efficiency and accuracy.
  • The company offers scalable AI solutions through modular, low-power chiplets.
  • d-Matrix focuses on brain-inspired AI compute engines for diverse inferencing workloads.

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Benefits

Hybrid Work Options

INACTIVE