RT Journal Article
T1 SWIMM 2.0: Enhanced Smith–Waterman on Intel’s Multicore and Manycore Architectures Based on AVX-512 Vector Extensions
A1 Rucci, Enzo
A1 De Giusti, Armando
A1 Naiouf, Marcelo
A1 García Sánchez, Carlos
A1 Botella Juan, Guillermo
A1 Prieto Matías, Manuel
AB The well-known Smith-Waterman (SW) algorithm is the most commonly used method for local sequence alignments, but its acceptance is limited by the computational requirements for large protein databases. Although theacceleration of SW has already been studied on many parallel platforms, there are hardly any studies which take advantage of the latest Intel architectures based on AVX-512 vector extensions. This SIMD set is currently supported byIntel’s Knights Landing (KNL) accelerator and Intel’s Skylake (SKL) general purpose processors. In this paper, we present an SW version that is optimized for both architectures: the renowned SWIMM 2.0. The novelty of this vectorinstruction set requires the revision of previous programming and optimization techniques. SWIMM 2.0 is based on a massive multi-threading and SIMD exploitation. It is competitive in terms of performance compared with otherstate-of-the-art implementations, reaching 511 GCUPS on a single KNL node and 734 GCUPS on a server equipped with a dual SKL processor. Moreover, these successful performance rates make SWIMM 2.0 the most efficient energyfootprint implementation in this study achieving 2.94 GCUPS/Watts on the SKL processor.
YR 2018
FD 2018-07-10
LK https://hdl.handle.net/20.500.14352/114023
UL https://hdl.handle.net/20.500.14352/114023
LA eng
DS Docta Complutense
RD 18 abr 2025