Keywords: Power-Flow analysis, electrical network, multiprocessor, High Performance Computing under constraint, OpenCL
Supervisor/contact: David Defour (david.defour'AT'univ-perp.fr)
Location: Perpignan/France Scientific
Context: Electrical network simulation monopolises considerable efforts in today's international community. Currently the networks are statically sized to the expected and projected demand and which is said to be completely accessible. The electrical network of the future, especially if one takes into account the needs of energy required by electrical vehicles, can no longer follow this model of full accessibility: indeed, vehicles' consumption will be highly correlated (peak hours - commuting between home and office in the mornings and evenings) and networks should be resized drastically to take these problems into account.
"Load flow" refers to the calculation of the distribution system according to the charges. If there are many projects or software for load flow simulation, none of them offer the performance to achieve a decent responsiveness. For example, in a given area, if 10 000 vehicles connect within 30 minutes, each vehicle would require a response within 20ms. This is not possible due to budget constraints as it would require the use of a supercomputer or a grid computer in every area that has to be considered (car park, city, region, ...).
Goal: The purpose of this thesis is to propose mechanisms that will lead to several implementations of the same algorithm regarding various objectives in the context of multicore architecture. As far as multicore architectures are concerned, improving performance is the main aim when developing applications such as the one presented above.
However new challenges need to be alleviated in order to achieve performance for a reasonable investment. These challenges can be represented by the trade-off between two conflicting goals. On one side, opacity is required to hide to the programmer unnecessary details about the hardware, the memory hierarchy and the communication network. On another side, visibility of the fundamental elements is necessary to let the programmer harness the power of today's multicore architectures.
However, additional constraints have to be taken into account. Among them, power consumption is nearly as important as performance. Usually the former is impacting the latter and vice versa. In this context, several implementations of the kernel should have to be considered depending on the targeted hardware or the workload of the architecture. This is kernel versioning.
The objectives of this thesis is to define a framework where it will be possible to extend the usual criteria that leads to multi-versioning with for example:
Hardware constraints: We are proposing to consider the usual constraints based on hardware characteristics, like memory, network interconnect and communication requirements of the application.
Context dependent constraints: For a given task several algorithms can be considered depending on the size of the data or the objectives to achieve (power, latency or bandwidth).
Regularity constraints: Regularity is essential when considering parallel applications. Depending on the architecture, we have to consider regularity on data structures, data values, execution or control.
Reliability constraints: Depending on the hardware, we may have a memory hierarchy with or without ECC. We may want to handle hardware errors that happen during computation by duplicating them either in time or in space according to the architecture.
Accuracy constraints: Multicore architectures make use of many floating-point units. These units implement the IEEE 754 standard, in which the 2008 revision introduces various representation formats, ranging from 16 to 128 bits. This encourages the adoption of mixed-precision in floating-point based algorithms.
Proposed implementations will be tested and validated by an industrial partner of this project.