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Future-Proof Data Systems in the Post-Moore Era

Project description

Data efficiency for tomorrow’s computing

As the volume of data skyrockets, existing computing infrastructures face immense pressure. This surge in demand coincides with a shift towards cloud computing, requiring data centres to enhance their efficiency. Compounding these challenges are the waning laws of computing, notably the end of Dennard scaling, prompting a critical push for hardware specialisation. These factors impact software development. With this in mind, the ERC-funded project FDS will create a new software infrastructure. It proposes innovative system software abstractions to optimise data-intensive job execution on modern hardware. By replacing traditional monolithic structures with a flexible optimisation and compilation framework, FDS aims to bridge the gap between data demand and compute capacity, driving efficiency and specialisation in resource-hungry data centres.

Objective

Three major trends put immense pressure on existing infrastructure. First, there is an increased demand for compute given the exponential growth of data volume we are collecting. Second, as most data- and compute-intensive systems move to the cloud, it is vital to make data-centers more efficient. Third, pressured by the waning laws of computing infrastructure (end of Dennard scaling and its impact on Moores' law) the hardware landscape has embarked on a major push towards specialization. Unsurprisingly, all of these have major implications on software development.

FDS addresses these challenges in a holistic fashion by establishing the foundations of a new software infrastructure. More specifically, I propose new system software abstractions that enable more efficient execution of data-intensive jobs on modern hardware; and new cost-models to support reasoning about the performance/resource efficiency trade-offs when scheduling the said workloads.
To enable development of future-proof data systems, I propose replacing the traditional monoliths of a logical-graph optimizer and execution engine, with a new flexible framework for optimization and compilation, and a runtime system that can exploit the features of modern hardware, but remains amenable to its evolving nature. Doing so requires innovation on many levels, and combines work from many layers of the system stack: from HW/SW co-design, to compilers, operating and runtime systems, databases and distributed systems.

It is a non-trivial undertaking, but it is a necessary one. And it will have big and lasting impact on academia, industry, and society. In fact, I strongly believe that the only way forward towards reducing the increasing gap between data- and compute-demand in resource-hungry data centers is a software-solution that boosts efficiency, embraces specialization, removes redundancy and optimizes for data movement. FDS will be the pioneering system leading the way.

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2024-STG

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Host institution

TECHNISCHE UNIVERSITAET MUENCHEN
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 496 305,00
Address
Arcisstrasse 21
80333 Muenchen
Germany

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Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 496 305,00

Beneficiaries (1)

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