Designer, Systems (Computer)

STARFIVE INTERNATIONAL PTE. LTD.; Pasir Panjang; On-site; MYR 100,000 - 150,000; Full time

Job summary

A technology company specializing in architecture improvements is seeking a qualified candidate to focus on micro-architectural design and machine learning. The role requires expertise in domain-specific accelerators and proficiency in C/C++. Candidates should have a strong understanding of various machine learning algorithms and execution models. The position is based in Pasir Panjang, Negeri Sembilan, Malaysia and offers an opportunity to independently drive modeling tasks in a collaborative environment.

Qualifications

• Understanding of mainstream GPGPU architecture and design choices.
• Knowledge of machine learning execution models in GPU/CPU.
• Proficiency in developing simulation-based performance models.

Responsibilities

• Understand and propose architecture improvements.
• Maintain confidence models for performance verification.
• Deliver high quality analysis/results independently.

Skills

Domain Specific Accelerators

Machine Learning Algorithms

C/C++

Scripting Languages (Perl/Python)

GPGPU Programming Models

AI Programming Frameworks

Education

BS/MS/PhD in a related field

Job description

Who are we?

We are the System Architecture Group at StarFive in Singapore. We focus on micro-architectural design, modeling, exploration and benchmarking. We help leadership and different stakeholders to make a data driven design decisions.

Job scope:

• Understand the mainstream GPGPU architecture and their design choice
• Using existing ML or HPC background to propose the possible architecture improvements and exploration possibilities
• Can deeply understand the programming model of each architecture and its impacts and influence on eco-system
• Maintain and build the confidence model for both verifying with software tools and profiling the performance so at to understand different architecture design choices

What are we looking for?

• BS/MS/PhD with relevant experience in Domain Specific Accelerators/Machine Learning
• Knowledge of different machine learning algorithms (eg: CNN, LSTM, DNN, GNN etc) and their execution model in GPU/CPU; understanding of parallel execution models like SIMD, SIMT etc
• Familiarity with GPGPU (eg: CUDA/OpenCL) programming models is preferred but not mandatory
• Any prior experience in developing simulation-based performance models for domain specific accelerators
• Proficient in C/C++ and scripting languages (Perl/Python)
• Knowledge in one or more AI programming frameworks – Tensorflow, Pytorch etc
• Knowledge of RISC-V ISA is valuable but not mandatory
• Ability to deliver high quality analysis/results and independently drive modeling tasks is preferred
• Curiosity and Enthusiasm to explore advance state of the art technologies with calculated risks
• Strong interpersonal skills, written and oral; good team player