The abstract of the talk reads as follows.

What Can We Learn Using Hardware Performance Monitors on Modern Microprocessors?

Modern microprocessors are ingenious pieces of technology, delivering tremendous amounts of computing power. Because of the complex design of current microprocessors, it is hard to understand how programs behave on them, how they attain the observed performance and what possible bottlenecks need to be dealt with. Usually, exploratory architectural simulation is used prior to implementing a design. However, once the chip has been built, such techniques provide little help to quickly gain insight into the actual behaviour of a program that executes on it: (i) although it can be massively parallelised, simulation remain several order of magnitude slower than execution on real hardware, while the simulated programs grow ever larger (both in memory footprint and in the number of instructions that are executed) during a (typical) run, (ii) getting a simulator to be cycle-accurate is a very complex problem. Moreover, to deliver high performance, a microprocessor contains a lot of components that are not necessary to ensure correct functional behaviour, such as caches, branch prediction, etc.

Benchmarking is one of the fundamental concepts in experimental computer science. Assessing the performance of a microprocessor running a number of benchmarks — or vice versa, understanding the performance of programs — is very important to enhance technology and validate research. For this reason, modern microprocessors are equipped with performance monitoring hardware. These monitors count the events as they occur in the processor during the execution of a program, for example the number of data cache misses, mispredicted branches, etc. This allows a researcher to identity commonly occurring events, and adapt his programs, tool chain, etc. to improve their performance in that aspect.

In this talk we will focus on the design of a modern super-scalar out-of-order processor, and the various components that allow it to operate with high performance. We will explain how the performance monitoring infrastructure can be used for gaining insight in the execution of a program. Because performance counters can leak information about the behaviour of a program, they can also be used as a side-channel to attack implementations of cryptographic algorithms. We will briefly outline an example of such an attack.

I have exported the Keynote presentation into a pdf file (8.9MB). It might not make too much sense without the explanation I would add when presenting, but you might learn a thing or two nonetheless. I hope

The event took place in the Arenberg Castle:

Coffee was served in a hall, where people long dead keep staring at you with jealous eyes that see all the delicious food pass by:

I must confess I understood little of the real cryptographical mojo people were preaching about;-)