Big data has revolutionized science and technology leading to the transformation of our
societies. High-performance computing (HPC) provides the necessary computational power …

The growing need for extracting information from large graphs has been pushing the
development of parallel graph algorithms. However, the highly irregular structure of the real …

High-performance computing requires a deep knowledge of the hardware platform to fully
exploit its computing power. The performance of data transfer between cores and memory is …

Thread‐level parallelism (TLP) has been widely exploited to optimize computational
resource usage in high‐performance systems. However, as many applications do not scale …

Parallel computing platforms are increasingly complex, with multiple cores, shared caches,
and NUMA memory interconnects, as well as asymmetric I/O access. Upcoming …

SUMMARY The popularity of Partitioned Global Address Space (PGAS) languages has
increased during the last years thanks to their high programmability and performance …

The increasing complexity of parallel computing platforms requires a deep knowledge of the
hardware and of the application needs. Locality a key criteria for performance optimization. It …

In this paper we analyze the energy overhead incurred when operating with data stored in
different levels of the memory subsystem (cache levels and DDR chips) of current multicore …

In this PhD thesis, we study algorithms and implementations to accelerate the solution of
dense linear systems by using hybrid architectures with multicore processors and …

We study the impact of non-uniform memory accesses (NUMA) on the solution of dense
general linear systems using an LU factorization algorithm. In particular we illustrate how an …