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Performance-Cost Trade-Offs in Heterogeneous Clouds

"Cloud infrastructures provide on-demand access to a large variety of computing devices
with different performance and cost. This creates many opportunities for cloud users to
run applications having complex resource requirements, starting from large numbers of
servers with low-latency interconnects, to specialized devices such as GPUs and FPGAs.
User expectations regarding the execution of applications may vary between the fastest
possible execution, the cheapest execution or any trade-off between the two extremes.
However, enabling cloud users to easily make performance-cost trade-offs is not a trivial
exercise and choosing the right amount and type of resources to run applications according
to user expectations is very difficult.
This thesis proposes three contributions to enable performance-cost trade-offs for
application execution in heterogeneous clouds by following two directions: make good use
of resources and make good choice of resources. We propose as a first contribution a
method to share FPGA-based accelerators in cloud infrastructures having the objective
to improve their utilization. As a second contribution we propose profiling methods to
automate the selection of heterogeneous resources for executing applications under user
objectives. Finally, we demonstrate how these technologies can be implemented and
exploited in heterogeneous cloud platforms."

Speaker: 
Ancuta IORDACHE (Myriads)
Date: 
Friday, 9. September 2016 - 11:00 to 13:00
Place: 
Auditorium du PNRB (batiment 9B, campus de Beaulieu)
Defense Type: 
Composition of jury: 
  • Alexander R. Wolf, Professeur, Imperial College London, rapporteur
  • Thilo Kielmann, Professeur associé, VU University Amsterdam, rapporteur
  • Lionel Seinturier, Professeur, Université de Lille 1, examinateur
  • François Taiani, Professeur, Université de Rennes 1, examinateur
  • Christine Morin, Directrice de Recherche, INRIA, examinateur
  • Guillaume Pierre, Professeur, Université de Rennes 1, directeur de thèse