PRUDA: An API for Time and Space Predictible Programming in NVDIA GPUs using CUDA

Reyyan Tekin , Houssam-Eddine Zahaf (1) , Giuseppe Lipari (1)

1 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189

Recent computing platforms combine CPUs with different types of accelerators such as Graphical Processing Units (GPUs) to cope with the increasing computation power needed by complex real-time applications. NVIDIA GPUs are compound of hundreds of computing elements called CUDA cores, to achieve fast computations for parallel applications. However, GPUs are not designed to support real-time execution , as their main goal is to achieve maximum through-put for their resources. Supporting real-time execution on NVIDIA GPUs involves not only achieving timely predictable calculations but also to optimize the CUDA cores usage. In this work, we present the design and the implementation of PRUDA (Predictable Real-time CUDA), a programming platform to manage the GPU resources, therefore decide when and where a real-time task is executed. PRUDA is written in C and provides different mechanisms to manage the task priorities and allocation on the GPU. It provides tools to help a designer to properly implement real-time schedulers on the top of CUDA.

Domaines: Systèmes embarqués; Système d'exploitation [cs.OS]

Reyyan Tekin, Houssam-Eddine Zahaf, Giuseppe Lipari. PRUDA: An API for Time and Space Predictible Programming in NVDIA GPUs using CUDA. Junior Workshop: JRWRTC - Real-Time Networks and Systems 2019, Nov 2019, Toulouse, France. ⟨hal-02408660⟩