CPU Workload Performance Analysis Engineer at Tenstorrent

United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Semiconductors, High-Performance ComputingIndustries

Requirements

Ph.D. in Computer Engineering, Electrical Engineering, or a related field
Strong research background or industry expertise in benchmark construction, workload characterization, workload reduction, and performance simulation
Proficiency in performance profiling tools such as Linux Perf, Strace, AMD’s uProf, Arm’s Telemetry Solution, or similar tools
Deep understanding of CPU microarchitecture concepts, including superscalar pipelines, speculative execution, SIMD, and memory hierarchy

Responsibilities

Conduct competitive analysis of the latest CPU products using industry-standard benchmarks and emerging applications
Characterize CPU workloads, identifying performance bottlenecks and power inefficiencies in hardware and software interactions
Collaborate with CPU architects and RTL designers to enhance microarchitectural features and improve performance/watt metrics
Reduce workloads for CPU performance modeling, FPGA emulation, and model-to-RTL correlation
Utilize performance models, EDA frameworks, and profiling tools to measure, characterize, and predict CPU performance and power under various workloads
Stay up to date with industry trends, new workload requirements, and advancements in CPU microarchitecture and performance analysis techniques

Skills

Key technologies and capabilities for this role

RISC-VCPU ArchitecturePerformance SimulationWorkload CharacterizationBenchmark ConstructionRTL DesignPerformance AnalysisPerformance ModelingPerformance Optimization

Questions & Answers

Common questions about this position

What is the salary for this CPU Workload Performance Analysis Engineer position?

This information is not specified in the job description.

Is this role remote or onsite, and where can I work from?

The role is onsite or remote in North America, open to locations including Santa Clara, CA, Austin, TX, Boston, MA, Toronto, ON, Ottawa, ON, or fully remote in North America.

What skills and qualifications are required for this role?

Requirements include a Ph.D. in Computer Engineering, Electrical Engineering, or related field; strong background in benchmark construction, workload characterization, and performance simulation; proficiency in tools like Linux Perf, Strace, AMD’s uProf, or Arm’s Telemetry; and deep knowledge of CPU microarchitecture concepts like superscalar pipelines and memory hierarchy.

What is the company culture like at Tenstorrent?

Tenstorrent values collaboration, curiosity, and a commitment to solving hard problems, with a diverse team of technologists passionate about AI and building the best AI platform.

What makes a strong candidate for this position?

Strong candidates have a Ph.D. in a relevant field, expertise in workload characterization and performance simulation, proficiency with performance profiling tools, and deep CPU microarchitecture knowledge; the role welcomes various experience levels assessed during interviews.

Tenstorrent

Builds advanced computers for AI applications

About Tenstorrent

Tenstorrent builds advanced computers specifically designed for artificial intelligence applications. Their products include high-performance computing systems that utilize specialized hardware and software solutions, leveraging technologies like ASIC design and RISC-V architecture. Unlike many competitors, Tenstorrent focuses on integrating neural network compilers into their systems, enhancing the efficiency of AI computations. The company's goal is to advance the capabilities of AI computing, serving clients in the AI and computing sectors while generating revenue through the sale of their specialized systems and services.

Toronto, CanadaHeadquarters

2016Year Founded

$1,297.7MTotal Funding

SERIES_DCompany Stage

Hardware, AI & Machine LearningIndustries

501-1,000Employees

Benefits

Hybrid Work Options

Risks

Competition from established AI hardware companies like Nvidia could impact market share.

Reliance on open-source software may delay product development timelines.

Geopolitical tensions in South Korea and Japan could disrupt Tenstorrent's supply chains.

Differentiation

Tenstorrent leverages RISC-V technology for flexible, open-source AI hardware solutions.

The company partners with BOS Semiconductors to develop next-gen automotive AI chips.

Tenstorrent's global presence includes offices in key tech hubs like Silicon Valley and Tokyo.

Upsides

RISC-V architecture's growth aligns with Tenstorrent's open-source AI software focus.

Automotive AI chip market growth offers lucrative opportunities for Tenstorrent's BOS partnership.

Increasing demand for HPC systems could expand Tenstorrent's reach beyond tech industries.

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