TabulaROSA: Tabular Operating System Architecture for Massively Parallel Heterogeneous Compute Engines
Jeremy Kepner, Ron Brightwell, Alan Edelman, Vijay Gadepally, Hayden, Jananthan, Michael Jones, Sam Madden, Peter Michaleas, Hamed Okhravi, Kevin, Pedretti, Albert Reuther, Thomas Sterling, Mike Stonebraker

TL;DR
TabulaROSA proposes a new massively parallel operating system architecture based on database principles and associative array algebra, demonstrating significant performance improvements over Linux on supercomputers.
Contribution
It introduces a mathematically rigorous, database-inspired operating system model that enables scalable, correct, and efficient management of massive parallel compute resources.
Findings
20x higher performance than Linux on supercomputers
Managed over 68 billion processes with 2000x more processes
Validated the approach through large-scale simulations
Abstract
The rise in computing hardware choices is driving a reevaluation of operating systems. The traditional role of an operating system controlling the execution of its own hardware is evolving toward a model whereby the controlling processor is distinct from the compute engines that are performing most of the computations. In this context, an operating system can be viewed as software that brokers and tracks the resources of the compute engines and is akin to a database management system. To explore the idea of using a database in an operating system role, this work defines key operating system functions in terms of rigorous mathematical semantics (associative array algebra) that are directly translatable into database operations. These operations possess a number of mathematical properties that are ideal for parallel operating systems by guaranteeing correctness over a wide range of…
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