Energy and power consumption are becoming critical metrics in the design and usage of
high performance systems. We have extended the Performance API (PAPI) analysis library …

Dense linear algebra (DLA) has historically been in the vanguard of software that must be
adapted first to hardware changes. This is because DLA is both critical to the accuracy and …

Gaussian Elimination is commonly used to solve dense linear systems in scientific models.
In a large number of applications, a need arises to solve many small size problems, instead …

The ongoing hardware evolution exhibits an escalation in the number, as well as in the
heterogeneity, of computing resources. The pressure to maintain reasonable levels of …

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 …

As modern hardware keeps evolving, an increasingly effective approach to developing
energy efficient and high-performance solvers is to design them to work on many small size …

For software to fully exploit the computing power of emerging heterogeneous computers, not
only must the required computational kernels be optimized for the specific hardware …

Currently, state of the art libraries, like MAGMA, focus on very large linear algebra problems,
while solving many small independent problems, which is usually referred to as batched …

The ongoing hardware evolution exhibits an escalation in the number, as well as in the
heterogeneity, of computing resources. The pressure to maintain reasonable levels of …

We propose two acceleration methods, namely, Fused and Gram, for reducing out‐of‐core
data access when performing randomized singular value decomposition (RSVD) on …