Voyager is an innovative computational resource designed by the San Diego Supercomputer Center in collaboration with technology partners to accelerate the development and performance of artificial intelligence and machine learning applications in science ...

There is a significant effort to increase the adoption of Deep Neural Networks (DNNs) in fields such as criminal justice and medicine. Yet, DNNs commonly fall short in these applications due to their "black box" nature. DNN research often focuses more ...

Experimental results are often plotted as 2-dimensional graphical plots (aka graphs) in scientific domains depicting dependent versus independent variables to aid visual analysis of processes. Repeatedly performing laboratory experiments consumes ...

We describe the design motivation, architecture, deployment, and early operations of Expanse, a 5 Petaflop, heterogenous HPC system that entered production as an NSF-funded resource in December 2020 and will be operated on behalf of the national ...

Most widely-deployed parallel file systems (PFSs) implement POSIX semantics, which implies sequential consistency for reads and writes. Strict adherence to POSIX semantics is known to impede performance and thus several new PFSs with relaxed consistency ...

Scientific applications often run for long periods of time, and as a result, frequently save their internal states to storage media in cases of unexpected interruptions (e.g., hardware failures). Emerging non-volatile memory (NVRAM) can write up to 40× ...

This article demonstrates an approach for combining general tuning techniques with the POWER8 hardware architecture through optimizing three representative stencil benchmarks. Two typical real-world applications, with kernels similar to those of the ...

The Sparse Matrix-Vector Multiplication (SpMV) kernel ranks among the most important and thoroughly studied linear algebra operations, as it lies at the heart of many iterative methods for the solution of sparse linear systems, and often constitutes a ...

The Comet petascale supercomputer was put into production as an XSEDE resource in early 2015 with the goal of serving a much larger user community than HPC systems of similar size. The Comet project set an audacious goal of reaching over 10,000 users in ...

Workflows have been traditionally a mean to describe and implement the computing experiments, usually parametric studies and explorations searching for the best solution, that scientific researchers want to perform. A workflow is not only the computing ...

The growing interest in being able to apply Big Data techniques to scientific data generated using HPC simulations led to the question of whether this is achievable on the same HPC platform, and if so, what is the performance that can be obtained on ...

Bioinformatics could greatly benefit from increased computational resources delivered by High Performance Computing. However, the decision-making about which is the best architecture to deliver good performance for a set of Bioinformatics applications ...

The emergence of cloud computing has brought the opportunity to use large-scale compute infrastructures for a broader and broader spectrum of applications and users. As the cloud paradigm gets attractive for the 'elasticity' in resource usage and ...

Massive computation power and storage capacity of cloud computing systems enable users to either store large generated scientific datasets in the cloud or delete and then regenerate them whenever reused. Due to the pay-as-you-go model, the more datasets ...

The growing computing power on leadership HPC systems is often accompanied by ever-escalating failure rates. Checkpointing is a common defensive mechanism used by scientific applications for failure recovery. However, directly writing the large and ...

After investigating the data processing characteristics of several scientific applications in various disciplines from bioinformatics to geology, we discover that they share one common feature: raw data is written once onto a storage system and then it ...

A broad range of physical phenomena in science and engineering can be explored using finite difference and volume based application codes. Incorporating Adaptive Mesh Refinement (AMR) into these codes focuses attention on the most critical parts of a ...

With the wide adoption of cloud computing, the scientific applications are migrated to cloud for execution. The complex structure of scientific applications bring challenges to optimization scheduling scientific applications across multiple ...

Cloud computing founds on the pay-per-use paradigm, and offers a simple way to acquire any kind of resources through an as-a-service approach. As a consequence, the cloud is currently seen as a viable and inexpensive alternative to customary parallel/...

NSF-funded computing centers have primarily focused on delivering high-performance computing resources to academic researchers with the most computationally demanding applications. But now that computational science is so pervasive, there is a need for ...