Sparse linear algebra is central to many scientific programs, yet compilers fail to optimize it
well. High-performance libraries are available, but adoption costs are significant. Moreover …

Heterogeneous systems with several kinds of devices, such as multi-core CPUs, GPUs,
FPGAs, among others, are now commonplace. Exploiting all these devices with device …

Current HPC clusters are composed by several machines with different computation
capabilities and different kinds and families of accelerators. Programming efficiently for …

Field‐programmable gate arrays (FPGAs) are an attractive type of accelerator for all‐
purpose high performance computing computing systems due to the possibility of deploying …

The scaling limitations of multi-core processor development have led to a diversification of
the processor cores used within individual computers. Heterogeneous computing has …

Scientific applications are some of the most computationally demanding software pieces.
Their core is usually a set of linear algebra operations, which may represent a significant …

The use of parallel computing systems frequently represents the only scalable way to solve
HPC (High performance Computing) problems in reasonable execution times. The current …

The use of parallel computing systems frequently represents the only scalable way to solve
HPC (High performance Computing) problems in reasonable execution times. The current …

Las rutinas de álgebra lineal BLAS son ampliamente utilizadas en aplicaciones científicas
de todo tipo. Existen implementaciones específicamente optimizadas para diferentes tipos …