MetaLab is a group of scientists who explore the properties of hardware and software systems at a meta level. With modern computer systems growing in complexity far beyond the ability of humans to reason about them, this means building machine-based capabilities to model, reason about and control these systems. Our group works on this problem in many different dimensions and across many application domains, ultimately aiming to build a complete fundamental understanding of how we can express and reason about all forms of computational system at a higher level. Members of the group have expertise in research areas spanning cloud computing, datacenters, many-core systems, networking, IoTs, middleware, compilers, and runtime optimisation.
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Best Paper Award at PACT 2017
Metalab researcher, Zheng Wang, has won the best paper award in The 26th International Conference on Parallel Architectures and Compilation
September 29, 2017Read more.
MetaLab Researcher wins EPSRC Grant to study Internet-slowing ‘stragglers’
Dr. Peter Garraghan has received funding from the EPSRC to model and predict stragglers within Internet-based distributed systems. The aim
June 13, 2017Read more.
UK-China Collaboration Reduces Datacenter Energy Consumption by 40%
MetaLab researcher Peter Garraghan in collaboration with Zhejiang University, China have proposed a new technique to dramatically reduce energy consumption of datacenters.
May 20, 2017Read more.
Lancaster Researcher Identifies Next Generation Failures in Digital Infrastructure
Computer scientists have long known about a phenomenon in cloud data centres called ‘stragglers’ that significantly slow down tasks. However,
March 15, 2017Read more.
Best Paper Award in CGO 2017!
Metalab researcher, Zheng Wang, has won the best paper award in The International Symposium on Code Generation and Optimization (CGO) 2017.
February 9, 2017Read more.
MetaLab researcher identifies Android pattern lock vulnerability
Our findings suggest that using Pattern Lock to protect sensitive information could actually be very risky. The popular Pattern Lock
January 23, 2017Read more.