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Phronix is introduced, a capability-centric learning paradigm that enables agentic harnesses to acquire, validate, and refine reusable capabilities from their own executions, significantly reducing solution non-determinism and improving reliability.
Modern High-Performance Computing workflows rely on Checkpoint/Restart (C/R) mechanisms for execution continuity, but their inherent task and data heterogeneity demands adaptability from the underlying C/R solution. In a case study with Montage, C/R with static configurations leads to an I/O overhead of $1.6 \times$ an...
Modern High Performance Computing (HPC) workloads exchange datasets at high velocity to enable data-driven science. HPC systems employ hardware and software I/O accelerators to enable efficient data exchange. However, domain scientists and software engineers must manually request specific hardware accelerators and manu...
WADO is presented, a distributed write-once-read-many (WORM) object-store runtime for data-centric workloads that closes this gap through three coordinated mechanisms: scope-centric processing, explicit pipeline decomposition, and interference-aware explicit parallelism.
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