In recent years approximate computing has been extensively explored as a paradigm to
design hardware and software solutions that save energy by trading off on the quality of the …

Context. Graphics processing unit (GPU) computing has become popular due to the
enormous calculation potential that can be harvested from a single card. The N-body …

Computer vision plays a crucial role in enabling connected autonomous vehicles (CAVs) to
observe and comprehend their surroundings. The computer vision tasks are typically based …

Mixed-precision computation, which uses multiple different precision in a single code, is
being studied to increase computational speed and energy efficiency. It typically uses the …

We introduce a mixed precision algorithm for computing sparse matrix-vector products and
use it to accelerate the solution of sparse linear systems by iterative methods. Our approach …

We propose a scheme for reduced-precision representation of floating point data on a
continuum between IEEE-754 floating point types. Our scheme enables the use of lower …

Mixed precision algorithms aim at taking advantage of the performance of low precisions
while maintaining the accuracy of high precision. In particular adaptive precision algorithms …

An era of exponentially improving computing efficiency is coming to an end as Moore's law
falters and Dennard scaling seems to have broken down. The power-wall obstacle fuels a …

Iterative solvers are frequently used in scientific applications and engineering computations.
However, the memory-bound Sparse Matrix-Vector (SpMV) kernel computation hinders the …

Data representation is the foundation in computing. Starting from Abacus to Super
Computers the representation of data decides the complexity (in terms of processing time …