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Open nowPosted 502 days ago

Performance Engineer (Workload Modelling and Simulation)

huaweiuk56 open roles

Where
Cambridge, United Kingdom
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Your applicationOpen nowPerformance Engineer (Workload Modelling and Simulation)huaweiuk · Cambridge, United Kingdom
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This job: posted 502 days ago

The posting

About Huawei Research and Development UK Limited

Founded in 1987, Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. We have 207,000 employees and operate in over 170 countries and regions, serving more than three billion people around the world.

Our vision and mission is to bring digital to every person, home and organization for a fully connected, intelligent world. To this end, we will drive ubiquitous connectivity and promote equal access to networks; bring cloud and artificial intelligence to all four corners of the earth to provide superior computing power where you need it, when you need it; build digital platforms to help all industries and organizations become more agile, efficient, and dynamic; redefine user experience with AI, making it more personalized for people in all aspects of their life, whether they’re at home, in the office, or on the go.

This spirit of innovation has led Huawei to work in close partnership with leading academic institutions in the UK to develop and refine the latest technologies. With a shared commitment to innovation and progress, both parties have worked together to achieve common goals and establish a strong partnership. The partnership between UK and Huawei help to develop the technologies of the future that will transform the way we all communicate, work and live.

For the past 30 years we have maintained an unwavering focus, rejecting shortcuts and easy opportunities that don't align with our core business. With a practical approach to everything we do, we concentrate our efforts and invest patiently to drive technological breakthroughs.

This strategic focus is a reflection of our core values:

  • staying customer-centric,
  • inspiring dedication,
  • persevering,
  • Growing by reflection

Huawei Research and Development UK Limited Overview

Huawei’s vision is a fully connected, intelligent world. To achieve this, we work to inspire passion for basic research around the world. Our combined passion drives development across the global innovation value chain. Huawei has the largest Research and Development organization in the world with 96,000+ employees in research centers around the globe. In the UK, we already have design centers in Cambridge, London, Edinburgh and Ipswich. We continue to explore and define new research directions and new services. We have expanded our collaborations with academic researchers; researched new network architectures, integration of communications and key enabling technologies; and developed the fundamental theories of these technologies. We invite you to join us on this exciting journey and drive your career forward.

Job Summary

We are seeking a highly motivated and enthusiastic Performance Engineer to join our dynamic workload modelling team. In this role, you will have the opportunity to work on cutting-edge projects involving performance projection, simulation, and architectural studies, with a focus on server CPUs, NPUs, and AI workloads. As a Performance Engineer, you will contribute to the development of performance models for upcoming server processors and accelerators, support architectural studies, and drive software/hardware co-optimization for next-generation systems.

Key Responsibilities:

  • Develop and enhance simulation features to enable rapid architectural exploration and performance evaluation of server CPUs and NPUs, focusing on AI and large-scale data analytics workloads.
  • Conduct in-depth performance projections for various workloads, including databases, distributed storage, and engines for AI and data analytics.
  • Contribute to architectural studies to explore and evaluate the latest server CPU core and SOC designs.
  • Work on characterizing workloads and developing methodologies for tracing and optimizing AI models to enhance simulation and performance analysis.
  • Construct a non-intrusive, highly accurate system for characterizing and modelling complex workloads, ensuring precise workload representation.
  • Collaborate with cross-functional teams to extract and analyze real-world workload features, contributing vital data for hardware development.

Person Specification:

  • Required:
  • Strong understanding of CPU architecture and micro-architecture performance techniques (e.g., branch prediction, prefetchers, cache hierarchies). Proficient in performance analysis and workload characterization, with hands-on experience in methodologies for system-level architectural exploration. Experience in developing using dynamic binary instrumentation infrastructures like QEMU or DynamoRIO or x86 PIN. Proficiency in C/C++, with a solid understanding of Assembly Language. Experience with Python and other scripting languages to support automation, data processing, and tool development. Excellent analytical and problem-solving skills with the ability to work both independently and as part of a team.
  • Desired:
  • Experience in compiler technologies, binary analysis, and performance tuning. Experience in developing and using performance simulators like GEM5 (O3 model), Sniper or others Knowledge of AI workloads and the challenges involved in optimizing large-scale models for performance simulation. Experience in Linux kernel development, including knowledge of kernel internals. Hands-on experience in CPU performance analysis, utilizing methodologies such as PMU-based profiling and TopDown Analysis, and proficiency with performance analysis tools like Linux perf.

What we offer

  • 33 days annual leave entitlement per year (including UK public holidays)
  • Group Personal Pension
  • Life insurance
  • Private medical insurance
  • Medical expense claim scheme
  • Employee Assistance Program
  • Cycle to work scheme
  • Company sports club and social events
  • Additional time off for learning and development
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