HPC applications are increasingly utilizing cloud resources due to their cost-effectiveness. Among these resources, spot compute instances present an opportunity to run applications at deep discounts compared to on-demand instances. However, they present unique challenges for tightly-coupled HPC applications due to potential interruptions. Traditional parallel programming models like MPI are not inherently fault-tolerant, and existing methods to handle these interruptions are inefficient and require significant programmer effort. In this paper, we present Charm++ as an alternative solution that natively supports fault tolerance, dynamic load balancing, and resource rescaling. We present a tool to run Charm++ applications with a mix of on-demand and spot instances which can detect and efficiently handle spot interruptions without a shared filesystem. We show that using spot instances can result in up to 60% cost savings for our benchmark application.

PySPH is an open-source, Python-based, framework for particle methods in general and Smoothed Particle Hydrodynamics (SPH) in particular. PySPH allows a user to define a complete SPH simulation using pure Python. High-performance code is generated from this high-level Python code and executed on either multiple cores, or on GPUs, seamlessly. It also supports distributed execution using MPI. PySPH supports a wide variety of SPH schemes and formulations. These include, incompressible and compressible fluid flow, elastic dynamics, rigid body dynamics, shallow water equations, and other problems. PySPH supports a variety of boundary conditions including mirror, periodic, solid wall, and inlet/outlet boundary conditions. The package is written to facilitate reuse and reproducibility. This article discusses the overall design of PySPH and demonstrates many of its features. Several example results are shown to demonstrate the range of features that PySPH provides.