Opendata, web and dolomites


Crosspoint In-memoRy CompUting Systems

Total Cost €


EC-Contrib. €






 CIRCUS project word cloud

Explore the words cloud of the CIRCUS project. It provides you a very rough idea of what is the project "CIRCUS" about.

instead    algorithms    plan    computation    execute    von    smartphones    memory    separation    realization    power    smart    group    learning    neumann    000x    cpu    business    efficiency    designed    financial    big    rescue    worldwide    cog    time    simulations    ready    classification    computing    erc    toward    machine    maturity    triple    digital    data    hence    operations    moving    physical    universal    accelerate    poc    poor    spread    transactions    limits    essentially    efficient    small    circus    architecture    frame    every    prediction    dangerous    computed    market    paradigm    conventional    consumption    industrial    investments    decade    recognize    centers    ml    computers    perform    breaking    demonstrating    techniques    consist    energy    modular    wealth    traffic    central    meantime    prototype    feasibility    search    optimally    monitor    solution    computer    scalability    stored    investor    regression    operated    inference    phones    disease   

Project "CIRCUS" data sheet

The following table provides information about the project.


Organization address
city: MILANO
postcode: 20133

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Italy [IT]
 Total cost 149˙463 €
 EC max contribution 149˙463 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2018-PoC
 Funding Scheme ERC-POC
 Starting year 2019
 Duration (year-month-day) from 2019-05-01   to  2020-10-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    POLITECNICO DI MILANO IT (MILANO) coordinator 149˙463.00


 Project objective

Every second, our smart phones deliver a wealth of information that can be used to monitor the traffic, the financial transactions, and even the spread of a dangerous disease. The processing of these big data into a meaningful information requires specific machine learning (ML) algorithms, which essentially consist of regression techniques for inference, classification and prediction. The conventional digital computers are not designed to optimally solve these problems with efficient time and energy consumption, which is one of the reasons why the power consumption by data centers worldwide is expected to triple in the next decade. Such a poor energy efficiency is essentially due to the physical separation between the central processing unit (CPU), where data are computed, and the memory, where data are stored, according to classical von Neumann computer architecture. In the frame of our ERC-CoG RESCUE, my group has developed a new paradigm to efficiently execute ML tasks in just one step within the memory. Instead of moving data from the memory to the digital CPU, an analogue computation is directly operated within the data, thus breaking all previous limits of time and energy consumption (10.000x reduction in the number of operations, hence time, and 1.000x in energy). Our in-memory technology is modular and universal, thus can be implemented in any existing memory and computing technology to accelerate ML tasks in future smartphones and data centers. In the ERC-PoC CIRCUS, we aim at bringing this technology to a higher maturity level, demonstrating its scalability and technical feasibility by simulations and realization of a small-scale prototype. In the meantime, we will also perform a comprehensive market search to recognize opportunities and draft an investor-ready business plan for raising future investments to further advance the solution toward industrial exploitation.

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The information about "CIRCUS" are provided by the European Opendata Portal: CORDIS opendata.

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