3 papers
cs.DC2022
Optimization of the Sparse Multi-Threaded Cholesky Factorization for A64FX
Valentin Le Fèvre, Tetsuzo Usui, Marc Casas
Sparse linear algebra routines are fundamental building blocks of a large variety of scientific applications. Direct solvers, which are methods for solving linear systems via the f…
cs.DC2020
Reducing Data Motion to Accelerate the Training of Deep Neural Networks
Sicong Zhuang, Cristiano Malossi, Marc Casas
This paper reduces the cost of DNNs training by decreasing the amount of data movement across heterogeneous architectures composed of several GPUs and multicore CPU devices. In par…
cs.LG2018
Low-Precision Floating-Point Schemes for Neural Network Training
Marc Ortiz, Adrián Cristal, Eduard Ayguadé +1
The use of low-precision fixed-point arithmetic along with stochastic rounding has been proposed as a promising alternative to the commonly used 32-bit floating point arithmetic to…