Publications

Showing 32 results for Author: Keita Teranishi

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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…

  • Aug, 2026

    Conference Paper

    Enabling Scientific Applications with Performance-Portability and High-Productivity for Multi-GPU Programming with JACC.Multi

    This work bridges the gap between multi-GPU computing and high-productivity, performance-portable programming solutions. Our goal is to enhance scientific applications with a productive and portable solution—program once, deploy everywhere—for multi-GPU programming with no cost to programmability. To accomplish this, we implemented JACC.Multi, which is part of the Julia fo…

  • Mar, 2026

    Conference Paper

    CHARM-SYCL & IRIS: A Tool Chain for Performance Portability on Extremely Heterogeneous Systems

    Performance portability is becoming crucial as high-performance computing systems become increasingly heterogeneous. We have many options for CPUs and accelerators (e.g., GPUs) but also for non-Von Neumann architectures such as field-programmable gate arrays. This paper presents the CHARM-SYCL unified programming environment for multiple accelerator types as a performance-…

  • 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

    Mojo: MLIR-based Performance-Portable HPC Science Kernels on GPUs for the Python Ecosystem

    We explore the performance and portability of the novel Mojo language for scientific computing workloads on GPUs. As the first language based on the LLVM’s Multi-Level Intermediate Representation (MLIR) compiler infrastructure, Mojo aims to close performance and productivity gaps by combining Python’s interoperability and CUDA-like syntax for compile-time portable GPU prog…

  • Mar, 2026

    Conference Paper

    Enhancing ChatPORT with CUDA-to-SYCL Kernel Translation Capability

    Large Language Models (LLMs) have shown strong capabilities in general code translation. However, code translation involving parallel programming models remains largely unexplored. This work enhances the capabilities of code LLMs in CUDA-to-SYCL kernel translation with parameter-efficient fine-tuning. The resultant fine-tuned LLM, called ChatPORT, is an effort to provide h…

  • Mar, 2026

    Conference Paper

    Extending SEER for Extreme Heterogeneity

    Heterogeneous and multi-device nodes are increasingly common in high-performance computing and data centers, yet existing programming models often lack simple, transparent, and portable support for these diverse architectures. The main contribution of this work is the development of novel SEER capabilities to address this challenge by providing a descriptive programming mo…

  • 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

    ChatPORT: Fine-Tuned LLM for Easy Code {PORT}ing

    Fine-tuning existing LLMs for specialized tasks has become a very attractive alternative due to its low cost and quick development cycle. With many pre-trained LLMs available, it is an increasingly complex task to choose the correct model as the starting point or base model. In this work we discuss ChatPORT - a specialized fine-tuned LLM geared towards providing correctly…

  • Mar, 2026

    Conference Paper

    Toward Automated Detection of Portability Bugs in Kokkos Parallel Programs

    Performance-portable programming frameworks provide abstractions for parallel execution to allow easily porting an application to multiple backend programming models, such as CUDA, HIP, and OpenMP. However, programs may still have portability bugs that manifest only on specific backends. Traditional testing is ineffective in discovering these bugs, as it would require conc…

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