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Big Data Analytics Using FPGAs

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  • Full or part time
    Dr Koch
  • Application Deadline
    Applications accepted all year round
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Large modern FPGAs provide more than 3000 dedicated multiplier blocks that can run at a speed of up to 500 MHz and the aggregated internal memory throughput can reach many terabytes per second. In the APT group, we are currently building an FPGA-based big data analytics machine that will harness the compute power of 2 large FPGAs, the aggregated throughput and capacity of 48 fast SSDs and a networking speed of 8 10Gb optical interconnects in a desktop form factor.

The goal of the project is to develop big data analytics applications for our new data analytics machine. The exact algorithms/application can be self-defined or will be given. Tasks may include, for example, histogram computation, text analytics, data clustering and/or data ranking and/or skyline queries (i.e. computing a Pareto-optimal data set).

Funding Notes

This School has two PhD programmes: the Centre for Doctoral Training (CDT) 4-year programme and a conventional 3-year PhD programme.

School and University funding is available on a competitive basis.


The minimum requirements to get a place in our PhD programme are available from:

How good is research at University of Manchester in Computer Science and Informatics?

FTE Category A staff submitted: 44.86

Research output data provided by the Research Excellence Framework (REF)

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