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.

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

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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