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We present the GPU implementation efforts and challenges of the sparse solver package STRUMPACK. The code is made publicly available on github with a permissive BSD license. STRUMPACK implements an approximate multifrontal solver, a sparse LU ...

Tuning algorithmic parameters to optimize the performance of large, complicated computational codes is an important problem involving finding the optima and identifying regimes defined by non-smooth boundaries in black-box functions. Within the Bayesian ...

Over the course of interactions with various application teams, the need for batched sparse linear algebra functions has emerged in order to make more efficient use of the GPUs for many small and sparse linear algebra problems. In this paper, we present ...

The U.S. Exascale Computing Project (ECP) has succeeded in preparing applications to run efficiently on the first reported exascale supercomputers in the world. To achieve this, it modernized the whole leadership software stack, from libraries to ...

This work is based on the seminar titled ‘Resiliency in Numerical Algorithm Design for Extreme Scale Simulations’ held March 1–6, 2020, at Schloss Dagstuhl, that was attended by all the authors. Advanced supercomputing is characterized by very high ...

Recent top-k computation efforts explore the possibility of revising various sorting algorithms to answer top-k queries on GPUs. These endeavors, unfortunately, perform significantly more work than needed. This paper introduces Dr. Top-k, a <u>D</u>...

The efficient utilization of mixed-precision numerical linear algebra algorithms can offer attractive acceleration to scientific computing applications. Especially with the hardware integration of low-precision special-function units designed for machine ...

Many applications require to learn, mine, analyze and visualize large-scale graphs. These graphs are often too large to be addressed efficiently using conventional graph processing technologies. Fortunately, recent research efforts find out graph ...

This article presents a low-rank decomposition algorithm based on subsampling of matrix entries. The proposed algorithm first computes rank-revealing decompositions of submatrices with a blocked adaptive cross approximation (BACA) algorithm, and then ...

We design and implement an efficient parallel algorithm for finding a perfect matching in a weighted bipartite graph such that weights on the edges of the matching are large. This problem differs from the maximum weight matching problem, for which scalable ...

We propose a new algorithm to improve the strong scalability of right-looking sparse LU factorization on distributed memory systems. Our 3D algorithm for sparse LU uses a three-dimensional MPI process grid, exploits elimination tree ...

• The 3D sparse LU factorization algorithm reduces the asymptotic communication complexity by ( log n ) for planar sparse matrices of dimension n and by a ...

Traffic flow prediction is a key component of an intelligent transportation system. Accurate traffic flow prediction provides a foundation for other tasks, such as signal coordination and travel time forecasting. There are many known methods in literature ...

We describe a modular software framework for solving user equilibrium traffic assignment problems. The design is based on the formulation of the problem as a variational inequality. Unlike most existing traffic assignment software which focus on specific ...

Compute efficiency is an important consideration for traffic flow prediction models. Machine learning algorithms adjust model parameters automatically based on the data, but often require users to set additional parameters, known as hyperparameters. ...

In the field of nanoparticle material science, X-ray scattering techniques are widely used for characterization of macromolecules and particle systems (ordered, partially-ordered or custom) based on their structural properties at the micro- and nano-...

With the continual development of multi and many-core architectures, there is a constant need for architecture-specific tuning of application-codes in order to realize high computational performance and energy efficiency, closer to the theoretical ...

The increasing gap between processor and memory performance has led to new architectural models for memory-intensive applications. In this paper, we use a set of memory-intensive benchmarks to evaluate a mixed logic and DRAM processor called VIRAM as a ...

Computer sim ulationsof realistic applications usually require solving a set of non-linear partial differential equations (PDEs) over a finite region. The process of obtaining numerical solutions to the governing PDEs involves solving large sparse ...