Dask enables parallel and out-of-core computation. We couple blocked algorithms with
dynamic and memory aware task scheduling to achieve a parallel and out-of-core NumPy …

Executing complex, burst-parallel, directed acyclic graph (DAG) jobs poses a major
challenge for serverless execution frameworks, which will need to rapidly scale and …

A new algebraic technique for the construction of interactive proof systems is presented. Our
technique is used to prove that every language in the polynomial-time hierarchy has an …

Datacenter disaggregation provides numerous benefits to both the datacenter operator and
the application designer. However switching from the server-centric model to a …

Most recent HPC platforms have heterogeneous nodes composed of multi-core CPUs and
accelerators, like GPUs. Programming such nodes is typically based on a combination of …

We present a sparse linear system solver that is based on a multifrontal variant of Gaussian
elimination and exploits low-rank approximation of the resulting dense frontal matrices. We …

Many scientific applications are conceptually built up from independent component tasks as
a parameter study, optimization, or other search. Large batches of these tasks may be …

The computation of the singular value decomposition, or SVD, has a long history with many
improvements over the years, both in its implementations and algorithmically. Here, we …

We present a method for developing dense linear algebra algorithms that seamlessly scales
to thousands of cores. It can be done with our project called DPLASMA (Distributed …

The emergence of accelerators as standard computing resources on supercomputers and
the subsequent architectural complexity increase revived the need for high-level parallel …