Node level heterogeneous architectures have become attractive during the last decade for
several reasons: compared to traditional symmetric CPUs, they offer high peak performance …

Parallel programming on SMP and multi-core architectures is hard. In this paper we present
a programming model for those environments based on automatic function level parallelism …

Clusters of GPUs are emerging as a new computational scenario. Programming them
requires the use of hybrid models that increase the complexity of the applications, reducing …

Programming models for multicore and many-core systems are listed as one of the main
challenges in the near future for computing research. These programming models should be …

While general-purpose homogeneous multi-core architectures are becoming ubiquitous,
there are clear indications that, for a number of important applications, a better …

Clusters of SMPs are ubiquitous. They have been traditionally programmed by using MPI.
But, the productivity of MPI programmers is low because of the complexity of expressing …

We discuss an algorithm that optimizes the driving style of a train. The objective is to
minimize the electrical energy used for traction subject to constraints such as the travel time …

State‐of‐the‐art dense linear algebra software, such as the LAPACK and ScaLAPACK
libraries, suffers performance losses on multicore processors due to their inability to fully …

We present a review of the current best practices in parallel programming models for dense
linear algebra (DLA) on heterogeneous architectures. We consider multicore CPUs, stand …

Asymmetric single-ISA multicore processors (AMPs), which integrate high-performance big
cores and low-power small cores, were shown to deliver higher performance per watt than …