Power & Performance
Reduce power consumption and maximize throughput with efficiency and performance optimization across all operating conditions.
Reduce power consumption and maximize throughput with efficiency and performance optimization across all operating conditions.
proteanTecs solutions are already embedded in production systems across high-performance industries, delivering real-world results in advanced nodes from 28nm to 2nm.
Don’t resort to worst-case and wasteful measures. Get the actionable visibility
needed to reduce power, boost performance, and cut cost at scale.
AVS Pro adjusts voltage to suit real-world performance, operational, and environmental requirements.
AVS Pro reduces average power in real time, with a safety net.
It measures the timing margin of millions of logic paths under actual workloads, and utilizes the operational voltage guard bands to reduce voltage to a minimum - at the operating frequency.

AVS Pro takes proactive measures to avoid failures that stem from workload fluctuations, temperature, voltage drops, noise, latent defects, and aging.
It provides real-time HW alerts for different timing margin threshold-crossing events to allow safe power reduction.
By reducing the nominal voltage throughout a chip’s life, AVS Pro lowers power consumption and temperature, reducing stress and delaying wearout.
As the chip ages, margins are optimized accordingly to ensure reliability while maximizing efficiency.
AFS Pro dynamically adjusts clock speeds under actual workloads and environmental conditions without risking functional failures.

Push beyond conventional frequency scaling methods and conservative guard bands by intelligently reclaiming unused timing margins in real time.
Leverage deep in-chip telemetry and machine learning to accurately predict VDDmin for static per-die VDD setting and tune operational settings at system test.
Personalized assessment
Lower max-power
Test time reduction
Cost reduction
Telemetry and ML based
Inline decisions at test
Predicts VDDmin using Profiling & Classification Agents, sensitive to process variance across all transistor types and standard cells.
A deep data machine learning solution allowing minimal steps for unmatched VDD setting accuracy, per device. Save time with only 1-2 search steps, instead of the conventional multi-step VDDmin search.
ML models are training on characterization data collected – leveraging Agent fusion, statistical analysis and advanced algorithms. Once validated, the training models are deployed to the edge software on the tester.
Integrates seamlessly into the test program and provides assessment on the test floor for real-time decisions.
Reduce VDDmin guard band between ATE, SLT and System Test based on timing-margin measurement.
Gain visibility into operational and environmental conditions, real workloads vs. structural test, and effects of voltage regulator and power supply.
Turn process variation into competitive advantage with intelligent, fine-grained power and performance binning based on true silicon characteristics.
Classify each chip with precision
Optimize power and performance per die
Enable smarter segmentation

AVS Pro is a closed-loop hardware-firmware application for reliability and functional-workload aware adaptive voltage scaling (AVS).
Discover how the fabless chipmaker used proteanTecs AVS Pro™ to dramatically reduce voltage guard bands with a failure-avoidance protection layer
An innovative approach to workload-aware and reliability-aware adaptive voltage scaling that is much safer than traditional methods. Therefore, it enables the use of fewer guard bands (i.e., reclaiming unutilized guard bands), to safely reduce power and significantly extend the lifespan of chips.
Mohit Gupta • SVP and GM, Custom Silicon and IP, Alphawave
Dr. Charlie Su • CTO and President, Andes Technology
Johnny Shen • President and CEO, AIchip Technologies
June Paik • CEO, FuriosaAI
Get answers to common questions about how proteanTecs reduces power, increases performance, and extends system life – all while maintaining reliable functionality.