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Avnet: Machine Learning Benchmarking on Low-Cost SBCs

Avnet: Machine Learning Benchmarking on Low-Cost SBCs

About This Training

From CPUs to DPUs and TPUs to GPUs, there is an ever-growing alphabet soup of specialized processor architectures. This, combined with the dozens of software frameworks available for machine learning, makes choosing the ideal combination for speed, power and accuracy an interesting task.

What are the most common ways of comparing inference on single-board computers that take into consideration the diversity of software and hardware available? Join us to explore results on MaaXBoard and other popular industry SBCs using the MLPerf suite for benchmarking.

Training Outline

Complete Session

What is Benchmarking and Why

Basic Benchmarking Roundup

What Benchmarks Already Exist for Inference at the Edge

Challenges of Benchmarking Inference at the Edge

Benchmarking Limitations/Use MLPerf in Practice/Conclusion

Presented by

Monica Houston
Software Engineer and Machine Learning Specialist, Avnet

MoreLess

DURATION

25 min

LANGUAGE

English

SKILL LEVEL

Beginner

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