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Master Thesis: Early Prediction and Optimization of power, Perfomance and Area

Ericsson AB
Ny

Sammanfattning

This opportunity involves a thesis project focused on improving early power, performance, and area (PPA) predictions in RTL designs for digital systems. The role requires working with RTL designs and associated data to establish baselines and analyze how design choices affect PPA. Candidates will explore various design structures and synthesis configurations, aiming to develop a methodology that provides actionable feedback to designers. This position is suitable for Master's students in related
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Det här erbjuder vi

Opportunity to shape the direction of the thesis project.Gain experience in semiconductor design, synthesis, and physical implementation flows.

Lund

Ansök senast: Öppet tillsvidare
Publicerad: 2026-11-03

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About this opportunity

Would you like to help digital design teams understand how an RTL design is likely to perform before completing time-consuming synthesis and physical implementation?

Power, performance and area, commonly referred to as PPA, are critical design objectives in advanced digital systems. However, reliable PPA results are often available only at a relatively late stage of the development process. At that point, addressing an inefficient architectural or RTL design choice may require significant redesign and repeated implementation runs.

Early estimates derived from RTL can differ considerably from final implementation results because they do not fully account for factors such as technology mapping, switching activity, buffering, placement and routing. In this thesis, you will investigate how RTL characteristics, simulation activity data and results from completed implementation runs can be combined to improve early PPA prediction. The goal is not only to produce more accurate estimates, but also to turn the findings into practical, actionable feedback for RTL and IP designers.

What you will do

You will work with one or more representative RTL designs and the associated simulation, synthesis, power and implementation data. You will establish PPA baselines and investigate how different RTL structures, architectural decisions and synthesis configurations affect power consumption, timing performance and silicon area.

You will have the opportunity to help shape the detailed direction of the thesis. Areas of investigation may include:

Correlating characteristics visible at RTL level with PPA results obtained after synthesis or physical implementation

Analysing the PPA impact of common design structures, including:

Multipliers and adders

Filters and multiplexers

Combinational and register-based logic

Pipelines, register placement and clock-gating opportunities

Comparing alternative RTL or architectural implementations that provide equivalent functionality

Evaluating synthesis configurations and optimisation priorities for power, timing and area

Using simulation activity data, such as VCD or FSDB data, to improve power analysis

Exploring data-driven, automated or AI-assisted methods for identifying PPA optimisation opportunities

Developing a reusable methodology or prototype flow that provides actionable feedback to RTL and IP designers

Verifying that proposed optimisations preserve functional correctness and satisfy relevant timing and area requirements

The expected outcome is a systematic and reusable approach for identifying PPA optimisation opportunities earlier in the development process. By moving this analysis closer to the RTL design stage, the work could improve PPA predictability, reduce manual investigation and limit the number of iterations between RTL development, synthesis and physical implementation.

The skills you bring

You are pursuing a Master's degree in Electrical Engineering, Computer Engineering, Computer Science, Embedded Systems or a related field

You have knowledge of digital design and computer architecture

You have a basic understanding of RTL design using Verilog, SystemVerilog or VHDL

You are interested in power, performance and area analysis

You can work methodically with experimental data and evaluate alternative design solutions

You are eager to learn about semiconductor design, synthesis and physical implementation flows

Experience in one or more of the following areas would be an advantage:

Logic synthesis or ASIC design flows
Digital simulation and waveform activity data
Scripting or programming using Python, Tcl or a similar language
Data analysis, machine learning or AI-assisted engineering methods

Ansök till tjänsten

Master Thesis: Early Prediction and Optimization of power, Perfomance and Area

Ny
Denna arbetsplats har annonserats på Ericsson-tjänsten den 2026-11-03 och publicerades av Ericsson.
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