In situ, steerable, hardware-independent and data-structure agnostic visualization with ISAAC

TL;DR

ISAAC is an in situ visualization library that allows scientific applications to visualize data directly on compute nodes with hardware independence, data-structure agnosticism, and support for user steering, streaming interactive videos remotely.

Contribution

The paper introduces ISAAC, a novel in situ visualization framework that operates independently of hardware and data structures, enabling live visualization and steering without data copying.

Findings

Supports arbitrary applications and metadata addition

Enables live visualization on compute nodes with hardware independence

Streams interactive visualization videos remotely

Abstract

The computation power of supercomputers grows faster than the bandwidth of their storage and network. Especially applications using hardware accelerators like Nvidia GPUs cannot save enough data to be analyzed in a later step. There is a high risk of loosing important scientific information. We introduce the in situ template library ISAAC which enables arbitrary applications like scientific simulations to live visualize their data without the need of deep copy operations or data transformation using the very same compute node and hardware accelerator the data is already residing on. Arbitrary meta data can be added to the renderings and user defined steering commands can be asynchronously sent back to the running application. Using an aggregating server, ISAAC streams the interactive visualization video and enables user to access their applications from everywhere.