GLASs: a GPU-accelerated Linear Algebra framework for exascaleproblems in physics and engineering
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We aim to present GLASs (GPU Library for Accelerated Solvers) as a lightweight, modular framework for implementing iterative solvers for large linear algebra problems on distributed GPU-accelerated systems. Its main design features are: •Easy to use templated class-based C++ interface, with Fortran bindings for easy integration with legacy codes•Lightweight client-library interaction through lambda expression arguments for solver operations •Custom BLAS-like independent modules for implementing compute-intensive operations •Options for performing mixed-precision computations, including NVIDIA’s bfloat16 half precision format •Easy switching between different communication backends, including NCCL •Communication calls performed on device data, enabling the use of GPUDirect RDMA where available
