Publications

Showing 29 results for Author: Aaron R. Young

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  • Sep, 2026

    Journal

    Accl++ : A high-productivity programming language for performance and code portability on heterogeneous systems

    This work describes the Accl++ programming language for heterogeneous computing. Accl++ is embedded in the C++ language and implemented as a C++ library. The language allows for describing device code and execution libraries and includes primitives for runtime compilation (RTC), thereby enabling code portability across disparate devices. Here, we demonstrate Accl++’s capab…

  • Sep, 2026

    Conference Paper

    IRIS-MASH: Efficient Multi-device Asynchronous Multi-Stream Heterogeneous Computing

    In the rapidly evolving field of high-performance computing (HPC), effectively leveraging heterogeneous devices through asynchronous task programming is paramount. This paper presents a robust asynchronous task programming model tailored for a multi-device, multi-stream execution environment that incorporates a diverse array of heterogeneous computing units, including GPUs…

  • Aug, 2026

    Conference Paper

    ChatHPC: Building the Foundations for a Productive and Trustworthy AI-Assisted HPC Ecosystem

    ChatHPC democratizes large language models for the high-performance computing (HPC) community by providing the infrastructure, ecosystem, and knowledge needed to apply modern generative AI technologies to rapidly create specific capabilities for critical HPC components while using relatively modest computational resources. Our divide-and-conquer approach focuses on creatin…

  • Jul, 2026

    Conference Paper

    PowerMappeR: Power-Optimized Mapping of SNNs onto ReRAM Crossbars coupled via Packet-Switched NoCs

    Many recent efforts in developing hardware-accelerated spiking neural networks (SNNs) are characterized by deep co-design between algorithms, architectures, and devices. Architectural advances overcome device constraints by coupling together many small resistive-RAM (ReRAM) crossbars via a network-on-chip (NoC) for neuromorphic component operation. Concurrently, improved S…

  • Mar, 2026

    Conference Paper

    IRIS: Exploring Performance Scaling of the Intelligent Runtime System and its Dynamic Scheduling Policies

    High-Performance Computing is becoming increasingly heterogeneous, relying on a diverse mix of hardware to achieve good performance. Paradoxically, current drivers and frameworks for these devices typically require separate languages and implementations for each vendor. Furthermore, there are few tools and little support to schedule codes between these devices in a truly h…

  • Mar, 2026

    Conference Paper

    ChatMPI: LLM-Driven MPI Code Generation for HPC Workloads

    The Message Passing Interface (MPI) standard plays a crucial role in enabling scientific applications for parallel computing and is an essential component in high-performance computing (HPC). However, implementing MPI code manually—especially applying a proper domain decomposition and communication pattern—is a challenging and error-prone task. We present ChatMPI, an AI as…

  • Mar, 2026

    Conference Paper

    ReSpike: A Co-Design Framework for Evaluating SNNs on ReRAM-Based Neuromorphic Processors

    With Moore’s law approaching its end, traditional von Neumann architectures are struggling to keep up with the exceeding performance and memory requirements of artificial intelligence and machine learning algorithms. Unconventional computing approaches such as neuromorphic computing that leverage spiking neural networks (SNNs) to perform computation are gaining traction an…

  • Mar, 2026

    Conference Paper

    Mapping Spiking Neural Networks to Heterogeneous Crossbar Architectures using Integer Linear Programming

    Advances in novel hardware devices and architectures allow Spiking Neural Network (SNN) evaluation using ultra-low power, mixed-signal, memristor crossbar arrays. As individual network sizes quickly scale beyond the dimensional capabilities of single crossbars, networks must be mapped onto multiple crossbars. Crossbar sizes within modern Memristor Crossbar Architectures (M…

  • Mar, 2026

    Conference Paper

    Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions

    We discuss the challenges and propose research directions for using AI to revolutionize the development of high-performance computing (HPC) software. AI technologies, in particular large language models, have transformed every aspect of software development. For its part, HPC software is recognized as a highly specialized scientific field of its own. We discuss the challen…

  • Mar, 2026

    Conference Paper

    IRIS-GNN: Leveraging Graph Neural Networks for Scheduling on Truly Heterogeneous Runtime Systems

    The diversity of accelerators in computer systems poses significant challenges for software developers, such as managing vendor-specific compiler toolchains, code fragmentation requiring different kernel implementations, and performance portability issues. To address these, the Intelligent Runtime System (IRIS) was developed. IRIS works across various systems, from smartph…

  • Mar, 2026

    Conference Paper

    Evolution at the Edge: Real-Time Evolution for Neuromorphic Engine Control

    Neuromorphic computing systems are attractive for real-time control at the edge because of their low power operation, real-time processing capabilities and their potential ability to do online learning. In this work, we describe an approach for performing real-time evolution of spiking neural networks for neuromorphic systems at the edge called Neuromorphic Optimization us…

  • Mar, 2026

    Conference Paper

    IRIS Reimagined: Advancements in Intelligent Runtime System for Task-Based Programming

    Task-based programming models are gaining traction in scientific computing. IRIS is a portable runtime system that exploits multiple heterogeneous programming systems and can discover available resources and manage multiple diverse programming systems (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, and OpenMP) simultaneously. It accounts for the constraints of task dependen…

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