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Vladimir Janjic

Researcher at University of St Andrews

Publications -  29
Citations -  176

Vladimir Janjic is an academic researcher from University of St Andrews. The author has contributed to research in topics: Thread (computing) & Multi-core processor. The author has an hindex of 8, co-authored 28 publications receiving 146 citations. Previous affiliations of Vladimir Janjic include University of Dundee & Andrews University.

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Proceedings ArticleDOI

RPL: A Domain-Specific Language for Designing and Implementing Parallel C++ Applications

TL;DR: This paper describes a method to semi-automatically generate and evaluate different parallelisations of the same application, allowing programmers to find the best parallelisation without significant manual reengineering of the code.
Proceedings ArticleDOI

Granularity-Aware Work-Stealing for Computationally-Uniform Grids

TL;DR: This paper shows how a basic ``Random-Stealing'' load balancing algorithm for computational Grids can be improved by using information about the task granularity of parallel programs, and proposes several strategies for using granularity information to improve load balancing.
Proceedings ArticleDOI

Agricultural Reform: More Efficient Farming Using Advanced Parallel Refactoring Tools

TL;DR: This work achieves speedups of up to 21 on a 24-core shared-memory system for a number of realistic use-cases using refactoring tool support that allows the programmer to introduce and tune parallelism in an easy and effective way.
Journal ArticleDOI

Collaborative Heterogeneity-Aware OS Scheduler for Asymmetric Multicore Processors

TL;DR: Colab as discussed by the authors is a general purpose asymmetry-aware scheduler targeting multi-threaded multi-programmed workloads, which estimates the performance and power of each thread on each type of core and identifies communication patterns and bottleneck threads.
Proceedings ArticleDOI

The SERUMS tool-chain: Ensuring Security and Privacy of Medical Data in Smart Patient-Centric Healthcare Systems

TL;DR: The design and initial implementation of the SERUMS tool-chain for accessing, storing, communicating and analysing highly confidential medical data in a safe, secure and privacy-preserving way is presented and a data fabrication framework for generating large volumes of synthetic but realistic data is described.