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From photons to big-data applications: terminating terabits.

Noa Zilberman¹, Andrew W Moore², Jon A Crowcroft²

¹Computer Laboratory, University of Cambridge, Cambridge, UK noa.zilberman@cl.cam.ac.uk.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences

|January 27, 2016

Summary

The growing network data volume surpasses current computer processing capacity. A new, multi-scale computer architecture is proposed to enhance scalability, reduce costs, save power, and boost performance.

Keywords:

computer architecture interconnect networking performance guarantees

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Area of Science:

Computer Architecture
Data Processing Systems
Networked Computing

Background:

The exponential growth of network data generation by user applications is outpacing the data-processing capabilities of individual computer end-systems.
Existing computer systems face scalability limitations due to the widening gap between networked data volume and per-system processing capacity.
Increasing demand for task variety and complexity in networked environments necessitates architectural innovation.

Purpose of the Study:

To critique the state-of-the-art in commodity computing concerning scalability benchmarks (e.g., terabits per second processing).
To propose a fundamental redesign of computer architectures and their ecosystems to address current limitations.
To outline a multi-scale approach for cost reduction, power savings, and performance enhancement.

Main Methods:

Analysis of current computer architectures and their limitations in handling large-scale network data.
Benchmarking against high-throughput processing requirements (terabits per second).
Conceptualization of a new architectural paradigm and its supporting ecosystem.

Main Results:

Identification of critical bottlenecks in current computer architectures for data-intensive applications.
Demonstration of the inadequacy of existing systems to meet future demands for scalability and performance.
A proposed architectural framework designed for efficiency and high throughput.

Conclusions:

Current computer architectures are at a critical juncture, unable to cope with escalating data demands.
A comprehensive re-evaluation of computer architecture design is essential for future scalability and capability.
The proposed multi-scale approach offers a pathway to more efficient, powerful, and cost-effective computing from nanoscale to data centers.