Search Results

Fortran's prominence in scientific computing requires strategies to ensure both that legacy codes are efficient on high-performance computing systems, and that the language remains attractive for the development of new high-performance codes. ...

• Intel Coarray Fortran with Nvidia CUDA Fortran and OpenMP allows parallel computing without extensive code redesign.
• Coarray Fortran offers comparable performance to the Message Passing Interface (MPI) for distributed memory ...

The integrated nested Laplace approximations (INLA) method has become a widely utilized tool for researchers and practitioners seeking to perform approximate Bayesian inference across various fields of application. To address the growing demand ...$_{}^{}$$_{}^{}$

Graphs model several real-world phenomena. With the growth of unstructured and semi-structured data, parallelization of graph algorithms is inevitable. Unfortunately, due to inherent irregularity of computation, memory access, and communication, ...

• Domain-specific language for graph algorithms.
• Targets multiple backends (CPU, GPU, distributed systems).
• Performance close to hand-tuned codes.

Parallelizing code in a shared-memory environment is commonly done utilizing loop scheduling (LS) in a fork-join manner as in OpenMP. This manner of parallelization is popular due to its ease to code, but the choice of the LS method is important when the ...

Increasing heterogeneity in HPC architectures and compiler advancements have led to OpenMP being frequently used to enable computations on heterogeneous devices. However, the efficient movement of data on heterogeneous computing platforms is crucial for ...

Data-parallel computations, such as linear algebra routines and stencil computations, constitute one of the most relevant classes in parallel computing, e.g., due to their importance for deep learning. Efficiently de-composing such computations for the ...

Parallel computing is essential for enhancing computational efficiency and advancing computational mechanics. To reduce the computational cost, peridynamics, a nonlocal numerical method, has been coupled with the finite element method (FEM). ...

• A plastic coupling of the finite element method and peridynamics is developed.
• The plastic coupling model is parallelized using OpenMP.
• A framework for the coupled code implementation using OpenMP is described.
• The coupling ...

Stencil calculations are a widely-used computing pattern, and tracking the performance of such computing pattern on modern GPGPUs is of interest to the computational community. In this document we focus on how directive-based programming models ...

Software developers must adapt to keep up with the changing capabilities of platforms so that they can utilize the power of High-Performance Computers (HPC), including exascale systems. OpenMP, a directive-based parallel programming model, allows ...

OpenMP, a widely adopted standard for shared memory parallel programming, is known for its simplicity and portability, making it accessible to programmers across various domains, not just HPC experts. This study aims at providing an overview of ...

Multipurpose caches can improve the throughput between the FPGA’s memory and the hardware that is generated when offloading OpenMP target regions. We discuss and evaluate the weaknesses (and also advantages) of different cacheing techniques in ...

MPI+X has been the de facto standard for distributed memory parallel programming. It is widely used primarily as an explicit two-sided communication model, which often leads to complex and error-prone code. Alternatively, PGAS model utilizes ...$\mathrm{}$$\mathrm{}$

The throughput-centric design of GPUs poses challenges when integrating them into time-sensitive applications. Nevertheless, modern GPU architectures and software have recently evolved, making it possible to minimize overheads and interference ...$\mathrm{}$

The OpenMP^® API offers both task-based and data-parallel concepts to scientific computing. While it provides descriptive and prescriptive annotations, it is in many places deliberately unspecific how to implement its annotations. As the ...

The Fortran programming language is prevalent in the scientific computing community with a wealth of existing software written in it. It is still being developed with the latest standard released in 2023. However, due to its long history, many old ...

This paper presents an approach to authoring a textbook titled Interactive OpenMP Programming with the assistance of Large Language Models (LLMs). The writing process utilized state-of-the-art LLMs, including Gemini Pro 1.5, Claude 3, and ChatGPT-...

This paper investigates the feasibility of using Large Language Models (LLMs) to identify semantically equivalent code snippets across different programming languages. Motivated by the need for cross-language translation datasets between OpenMP ...

Performance optimization continues to be a challenge in modern HPC software. Existing performance optimization techniques, including profiling-based and auto-tuning techniques, fail to indicate program modifications at the source level thus ...

The Clacc project has developed OpenACC compiler, runtime, and profiling interface support for C/C++ by extending Clang and LLVM. A key Clacc design feature is that it translates OpenACC to OpenMP to leverage the OpenMP offloading support that is ...

Large language models (LLMs)such as ChatGPT have significantly advanced the field of Natural Language Processing (NLP). This trend led to the development of code-based large language models such as StarCoder, WizardCoder, and CodeLlama, which are ...