Computer Architecture Team

The paper presents an algorithm for scheduling parallel programs for execution in a parallel architecture based on dynamic SMP processor clusters with data transfers on the fly. The algorithm is based on the concept of moldable computational tasks. First, an initial program graph is decomposed into sub-graphs, which are then treated as moldable tasks. So identified moldable tasks are then scheduled using an algorithm with warranted schedule length.

This paper presents a new version of the dynamic SMP cluster -based architecture oriented towards networks on chip implementation technique. Smaller sub-networks with many dynamic SMP clusters and communication on the fly are connected by a central global network. Processors are provided with multi-ported data caches that enable parallel data transactions with memory modules, including parallel data pre-fetching and communication

Expressing attack-defence trees in a multi-agent setting allows for studying a new aspect of security scenarios, namely how the number of agents and their task assignment impact the performance, e.g. attack time, of strategies executed by opposing coalitions. Optimal scheduling of agents’ actions, a non-trivial problem, is thus vital. We discuss associated caveats and propose an algorithm that synthesises such an assignment, targeting minimal attack time and using minimal number of agents for a given attack-defence tree. The complexity of the algorithm is proved to be quadratic in the number of the attack-defence tree nodes.

The paper presents a comparative analysis of parallel implementation of the preconditioned conjugate gradient method with the symmetric-successive over-relaxation preconditioner. Two parallel implementations of the matrix solver are compared. The first one is a message-passing version executed on a cluster of workstations. The other one is an efficient version simulated on a novel architecture of dynamically reconfigurable shared memory clusters with a new paradigm of inter-processor communication called communication on the fly. The presented example shows high suitability of the proposed architecture for fine grain numerical computations. It can be very useful in the simulation of physical phenomena described as numerical problems suitable for fine grain parallel execution.

Expressing attack-defence trees in a multi-agent setting allows for studying a new aspect of security scenarios, namely how the number of agents and their task assignment impact the performance, e.g. attack time, of strategies executed by opposing coalitions. Optimal scheduling of agents' actions, a non-trivial problem, is thus vital. We discuss associated caveats and propose an algorithm that synthesises such an assignment, targeting minimal attack time and using the minimal number of agents for a given attack-defence tree. We also investigate an alternative approach for the same problem using Rewriting Logic, starting with a simple and elegant declarative model, whose correctness (in terms of schedule's optimality) is self-evident. We then refine this specification, inspired by the design of our specialised algorithm, to obtain an efficient system that can be used as a playground to explore various aspects of attack-defence trees. We compare the two approaches on different benchmarks.