Skip to main content
Top
Published in: Datenbank-Spektrum 1/2018

02-02-2018 | Kurz erklärt

Diversity of Processing Units

An Attempt to Classify the Plethora of Modern Processing Units

Authors: Wolfgang Lehner, Annett Ungethüm, Dirk Habich

Published in: Datenbank-Spektrum | Issue 1/2018

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Recent hardware developments are providing a plethora of alternatives to well-known general-purpose processing units. This development reaches into all major directions, i.e., into high-speed and low latency communications systems, novel memory components as well as a zoo of different processing units in addition to the traditional CPU-style processors. While all developments have great impact on the design of database systems, we will try—in the context of this Kurz Erklärt—to categorize recent advances in the context of processing units and comment on the impact on database systems.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Show more products
Literature
1.
go back to reference Agrawal SR, Idicula S, Raghavan A, Vlachos E, Govindaraju V, Varadarajan V, Balkesen C, Giannikis G, Roth C, Agarwal N, Sedlar E (2017) A many-core architecture for in-memory data processing. In: MICRO, pp 245–258 Agrawal SR, Idicula S, Raghavan A, Vlachos E, Govindaraju V, Varadarajan V, Balkesen C, Giannikis G, Roth C, Agarwal N, Sedlar E (2017) A many-core architecture for in-memory data processing. In: MICRO, pp 245–258
2.
go back to reference Barthels C, Loesing S, Alonso G, Kossmann D (2015) Rack-scale in-memory join processing using rdma. In: SIGMOD, pp 1463–1475 Barthels C, Loesing S, Alonso G, Kossmann D (2015) Rack-scale in-memory join processing using rdma. In: SIGMOD, pp 1463–1475
3.
go back to reference Damme P, Habich D, Hildebrandt J, Lehner W (2017) Lightweight data compression algorithms: an experimental survey (experiments and analyses). In: EDBT, pp 72–83 Damme P, Habich D, Hildebrandt J, Lehner W (2017) Lightweight data compression algorithms: an experimental survey (experiments and analyses). In: EDBT, pp 72–83
4.
go back to reference Dreseler M, Kissinger T, Dürken T, Lüubke E, Uflacker M, Habich D, Plattner H, Lehner W (2017) Hardware-accelerated memory operations on large-scale numa systems. In: ADMS@VLDB Dreseler M, Kissinger T, Dürken T, Lüubke E, Uflacker M, Habich D, Plattner H, Lehner W (2017) Hardware-accelerated memory operations on large-scale numa systems. In: ADMS@VLDB
7.
go back to reference Haas S, Arnold O, Nöthen B, Scholze S, Ellguth G, Dixius A, Höppner S, Schiefer S, Hartmann S, Henker S et al (2016) An mpsoc for energy-efficient database query processing. In: DAC, pp 1–6 Haas S, Arnold O, Nöthen B, Scholze S, Ellguth G, Dixius A, Höppner S, Schiefer S, Hartmann S, Henker S et al (2016) An mpsoc for energy-efficient database query processing. In: DAC, pp 1–6
8.
go back to reference Haas S, Scholze S, Höppner S, Ungethüm A, Mayr C, Schüffny R, Lehner W, Fettweis G (2017) Application-specific architectures for energy-efficient database query processing and optimization. Microprocess Microsyst 55:119–130CrossRef Haas S, Scholze S, Höppner S, Ungethüm A, Mayr C, Schüffny R, Lehner W, Fettweis G (2017) Application-specific architectures for energy-efficient database query processing and optimization. Microprocess Microsyst 55:119–130CrossRef
15.
go back to reference Karnagel T, Habich D (2017) Heterogeneous placement optimization for database query processing. it Inf Technol 59(3):117 Karnagel T, Habich D (2017) Heterogeneous placement optimization for database query processing. it Inf Technol 59(3):117
16.
go back to reference Karnagel T, Habich D, Lehner W (2017) Adaptive work placement for query processing on heterogeneous computing resources. Proceedings VLDB Endowment 10(7):733–744CrossRef Karnagel T, Habich D, Lehner W (2017) Adaptive work placement for query processing on heterogeneous computing resources. Proceedings VLDB Endowment 10(7):733–744CrossRef
17.
go back to reference Kissinger T, Habich D, Lehner W (2018) Adaptive energy-control for in-memory database systems. In: SIGMOD Kissinger T, Habich D, Lehner W (2018) Adaptive energy-control for in-memory database systems. In: SIGMOD
18.
go back to reference Lehner W (2017) The data center under your desk – how disruptive is modern hardware for db system design? Proceedings VLDB Endowment 10(12):2018–2019CrossRef Lehner W (2017) The data center under your desk – how disruptive is modern hardware for db system design? Proceedings VLDB Endowment 10(12):2018–2019CrossRef
19.
go back to reference Li F, Das S, Syamala M, Narasayya VR (2016) Accelerating relational databases by leveraging remote memory and rdma. In: SIGMOD, pp 355–370CrossRef Li F, Das S, Syamala M, Narasayya VR (2016) Accelerating relational databases by leveraging remote memory and rdma. In: SIGMOD, pp 355–370CrossRef
22.
go back to reference Oukid I, Kettler R, Willhalm T (2017) Storage class memory and databases: opportunities and challenges. it Inf Technol 59(3):109 Oukid I, Kettler R, Willhalm T (2017) Storage class memory and databases: opportunities and challenges. it Inf Technol 59(3):109
23.
go back to reference Salama A, Binnig C, Kraska T, Scherp A, Ziegler T (2017) Rethinking distributed query execution on high-speed networks. IEEE Data Eng Bull 40(1):27–37 Salama A, Binnig C, Kraska T, Scherp A, Ziegler T (2017) Rethinking distributed query execution on high-speed networks. IEEE Data Eng Bull 40(1):27–37
26.
go back to reference Teubner J (2017) Fpgas for data processing: current state. it Inf Technol 59(3):125–131 Teubner J (2017) Fpgas for data processing: current state. it Inf Technol 59(3):125–131
27.
go back to reference Ungethüm A, Kissinger T, Mentzel W, Habich D, Lehner W (2016) Energy elasticity on heterogeneous hardware using adaptive resource reconfiguration LIVE. In: SIGMOD, pp 2173–2176CrossRef Ungethüm A, Kissinger T, Mentzel W, Habich D, Lehner W (2016) Energy elasticity on heterogeneous hardware using adaptive resource reconfiguration LIVE. In: SIGMOD, pp 2173–2176CrossRef
28.
go back to reference Willhalm T, Popovici N, Boshmaf Y, Plattner H, Zeier A, Schaffner J (2009) Simd-scan: ultra fast in-memory table scan using on-chip vector processing units. Proceedings VLDB Endowment 2(1):385–394CrossRef Willhalm T, Popovici N, Boshmaf Y, Plattner H, Zeier A, Schaffner J (2009) Simd-scan: ultra fast in-memory table scan using on-chip vector processing units. Proceedings VLDB Endowment 2(1):385–394CrossRef
29.
go back to reference Woods L, Istvan Z, Alonso G (2013a) Hybrid fpga-accelerated sql query processing. In: FPL, pp 1–1 Woods L, Istvan Z, Alonso G (2013a) Hybrid fpga-accelerated sql query processing. In: FPL, pp 1–1
30.
go back to reference Woods L, Teubner J, Alonso G (2013b) Less watts, more performance: an intelligent storage engine for data appliances. In: SIGMOD, pp 1073–1076 Woods L, Teubner J, Alonso G (2013b) Less watts, more performance: an intelligent storage engine for data appliances. In: SIGMOD, pp 1073–1076
33.
go back to reference Young J, Wu H, Yalamanchili S (2012) Satisfying data-intensive queries using GPU clusters. In: SC companion: high performance computing, networking storage and analysis, p 1314 Young J, Wu H, Yalamanchili S (2012) Satisfying data-intensive queries using GPU clusters. In: SC companion: high performance computing, networking storage and analysis, p 1314
34.
go back to reference Ziener D, Bauer F, Becher A, Dennl C, Meyer-Wegener K, Schürfeld U, Teich J, Vogt JS, Weber H (2016) Fpga-based dynamically reconfigurable sql query processing. ACM Trans Reconfigurable Technol Syst 9(4) Ziener D, Bauer F, Becher A, Dennl C, Meyer-Wegener K, Schürfeld U, Teich J, Vogt JS, Weber H (2016) Fpga-based dynamically reconfigurable sql query processing. ACM Trans Reconfigurable Technol Syst 9(4)
Metadata
Title
Diversity of Processing Units
An Attempt to Classify the Plethora of Modern Processing Units
Authors
Wolfgang Lehner
Annett Ungethüm
Dirk Habich
Publication date
02-02-2018
Publisher
Springer Berlin Heidelberg
Published in
Datenbank-Spektrum / Issue 1/2018
Print ISSN: 1618-2162
Electronic ISSN: 1610-1995
DOI
https://doi.org/10.1007/s13222-018-0276-y

Other articles of this Issue 1/2018

Datenbank-Spektrum 1/2018 Go to the issue

Community

News

Editorial

Editorial

Premium Partner