1 citations · 2 across the 15 of their papers we have counts for
17 papers
The Case of the Mysterious Citations
Amanda Bienz, Carl Pearson, Simon Garcia de Gonzalo
Mysterious citations are routinely appearing in peer-reviewed publications throughout the scientific community. In this paper, we developed an automated pipeline and examine the pr…
Scaling All-to-all Operations Across Emerging Many-Core Supercomputers
Shannon Kinkead, Jackson Wesley, Whit Schonbein +3
Performant all-to-all collective operations in MPI are critical to fast Fourier transforms, transposition, and machine learning applications. There are many existing implementation…
Persistent and Partitioned MPI for Stencil Communication
Gerald Collom, Jason Burmark, Olga Pearce +1
Many parallel applications rely on iterative stencil operations, whose performance are dominated by communication costs at large scales. Several MPI optimizations, such as persiste…
Optimizing Allreduce Operations for Modern Heterogeneous Architectures with Multiple Processes per GPU
Michael Adams, Amanda Bienz
Large inter-GPU all-reduce operations, prevalent throughout deep learning, are bottlenecked by communication costs. Emerging heterogeneous architectures are comprised of complex no…
MPI Advance : Open-Source Message Passing Optimizations
Amanda Bienz, Derek Schafer, Anthony Skjellum
The large variety of production implementations of the message passing interface (MPI) each provide unique and varying underlying algorithms. Each emerging supercomputer supports o…
A More Scalable Sparse Dynamic Data Exchange
Andrew Geyko, Gerald Collom, Derek Schafer +2
Parallel architectures are continually increasing in performance and scale, while underlying algorithmic infrastructure often fail to take full advantage of available compute power…
Collective-Optimized FFTs
Evelyn Namugwanya, Amanda Bienz, Derek Schafer +1
This paper measures the impact of the various alltoallv methods. Results are analyzed within Beatnik, a Z-model solver that is bottlenecked by HeFFTe and representative of applicat…
Optimizing Irregular Communication with Neighborhood Collectives and Locality-Aware Parallelism
Gerald Collom, Rui Peng Li, Amanda Bienz
Irregular communication often limits both the performance and scalability of parallel applications. Typically, applications individually implement irregular messages using point-to…
Characterizing the Performance of Node-Aware Strategies for Irregular Point-to-Point Communication on Heterogeneous Architectures
Shelby Lockhart, Amanda Bienz, William D. Gropp +1
Supercomputer architectures are trending toward higher computational throughput due to the inclusion of heterogeneous compute nodes. These multi-GPU nodes increase on-node computat…
A Locality-Aware Bruck Allgather
Amanda Bienz, Shreeman Gautam, Amun Kharel
Collective algorithms are an essential part of MPI, allowing application programmers to utilize underlying optimizations of common distributed operations. The MPI_Allgather gathers…
Performance Analysis and Optimal Node-Aware Communication for Enlarged Conjugate Gradient Methods
Shelby Lockhart, Amanda Bienz, William Gropp +1
Krylov methods are a key way of solving large sparse linear systems of equations, but suffer from poor strong scalabilty on distributed memory machines. This is due to high synchro…
Modeling Data Movement Performance on Heterogeneous Architectures
Amanda Bienz, Luke N. Olson, William D. Gropp +1
The cost of data movement on parallel systems varies greatly with machine architecture, job partition, and nearby jobs. Performance models that accurately capture the cost of data…
Node-Aware Improvements to Allreduce
Amanda Bienz, Luke N. Olson, William D. Gropp
The \texttt{MPI\_Allreduce} collective operation is a core kernel of many parallel codebases, particularly for reductions over a single value per process. The commonly used allredu…
Reducing Communication in Algebraic Multigrid with Multi-step Node Aware Communication
Amanda Bienz, Luke Olson, William Gropp
Algebraic multigrid (AMG) is often viewed as a scalable solver for sparse linear systems. Yet, parallel AMG lacks scalability due to increasingly large costs assoc…
Improving Performance Models for Irregular Point-to-Point Communication
Amanda Bienz, William D. Gropp, Luke N. Olson
Parallel applications are often unable to take full advantage of emerging parallel architectures due to scaling limitations, which arise due to inter-process communication. Perform…
Node Aware Sparse Matrix-Vector Multiplication
Amanda Bienz, William D. Gropp, Luke N. Olson
The sparse matrix-vector multiply (SpMV) operation is a key computational kernel in many simulations and linear solvers. The large communication requirements associated with a refe…
Reducing Parallel Communication in Algebraic Multigrid through Sparsification
Amanda Bienz, Robert D. Falgout William Gropp, Luke N. Olson +1
Algebraic multigrid (AMG) is an solution process for many large sparse linear systems. A hierarchy of progressively coarser grids is constructed that utilize compl…