Abstract
Distributed storage systems utilize erasure codes to reduce their storage costs while efficiently handling failures. Many of these codes (e. g., Reed-Solomon (RS) codes) rely on Galois Field (GF) arithmetic, which is considered to be fast when the field characteristic is 2. Nevertheless, some developments in the field of erasure codes offer new efficient techniques that require mostly XOR operations, and are thus faster than GF operations. Recently, Intel announced [1] that its future architecture (codename 'Ice Lake') will introduce new set of instructions called Galois Field New Instruction (GF-NI). These instructions allow software flows to perform vector and matrix multiplications over GF (28) on the wide registers that are available on the AVX512 architectures. In this paper, we explain the functionality of these instructions, and demonstrate their usage for some fast computations in GF(28). We also use the Intel® Intelligent Storage Acceleration Library (ISA-L) in order to estimate potential future improvement for erasure codes that are based on RS codes. Our results predict approx 1.4x speedup for vectorized multiplication, and 1.83x speedup for the actual encoding.
Original language | English |
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Title of host publication | Proceedings of the 25th International Symposium on Computer Arithmetic, ARITH 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 125-129 |
Number of pages | 5 |
ISBN (Print) | 9781538626122 |
DOIs | |
State | Published - 13 Sep 2018 |
Event | 25th International Symposium on Computer Arithmetic, ARITH 2018 - Amherst, United States Duration: 25 Jun 2018 → 27 Jun 2018 |
Publication series
Name | Proceedings - Symposium on Computer Arithmetic |
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Volume | 2018-June |
Conference
Conference | 25th International Symposium on Computer Arithmetic, ARITH 2018 |
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Country/Territory | United States |
City | Amherst |
Period | 25/06/18 → 27/06/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
ASJC Scopus subject areas
- Theoretical Computer Science
- Software
- Hardware and Architecture