This paper proposes a thermodynamic computing stack for machine learning using stochastic analog processes and energy-based models.

This paper presents the first application of thermodynamic computing to mRNA codon optimization in pharmaceutical R&D, achieving significant energy savings compared to conventional GPUs.

The paper introduces a unified Physics-Informed Deep Learning (PIDL) framework that simultaneously enforces physical laws and information-theoretic bounds, demonstrating robust, domain-agnostic entrop…

The paper introduces Grid Programs, a novel, Turing-complete model of computation where programs are two-dimensional arrangements of instructions, fundamentally departing from linear code structures.

This paper proposes a method to describe dynamical systems using molecular and reaction concepts, making three key decisions: number of places, species determination, and transitions.

This paper studies the autarky problem of scheduling energy-consuming jobs with time windows using a battery and an energy forecast, and shows NP-hardness, polynomial-time solvability, and fixed-param…

The paper introduces an improved PULSE method to efficiently estimate the thermodynamic properties of chemically disordered compounds by sampling and estimating the system's partition function, demons…

This paper introduces a streaming model with catalytic memory and shows dramatic space savings for data stream algorithms, providing exact computation of frequency moments using multi-pass algorithms…

This paper measures the lower bound for the shortest program generating a sequence, proving a conservation law and providing a deterministic engine to recover generating programs for certain sequences…

This paper investigates the thermal constraints of deploying AI compute infrastructure in space, comparing GPUs and compute-in-memory (CIM) accelerators using a co-design methodology.

The paper introduces Exa-PD, a highly parallelizable workflow for constructing multi-element phase diagrams using MD and MC simulations, coordinated by Parsl, and CALPHAD modeling.

The paper proposes the Intelligent Computing Architecture Model (ICAM), a six-layer framework that unifies disparate concepts in model-native computing by viewing the LLM stack through a dual-plane ar…

This paper introduces a novel algorithm for generating k Hamming weight binary words in linear time while minimizing random bit consumption.

Researchers used a large language model to generate checkpoint/restart code for MPI applications, achieving comparable efficiency to human-engineered solutions.

The paper proposes an Entropy Dynamics framework to analyze the stability and failure modes of centralized orchestration in Multi-Agent Systems, identifying a 'Reasoning Trap' where complex reasoning…

This paper introduces Ichnos+, a system to estimate the environmental footprint of Nextflow scientific workflows using post-hoc analysis and node-specific power models.

The paper presents the Quantum Resource Management Interface (QRMI) as a standardized, vendor-agnostic middleware layer for integrating quantum resources into high-performance computing environments,…