Approximate Computing (APPROXC)5 ECTS
(englische Bezeichnung: Approximate Computing)
(Prüfungsordnungsmodul: Approximate Computing)

Lehrveranstaltungen:

• • Approximate Computing
    (Vorlesung, 2 SWS, Oliver Keszöcze et al., Do, 14:15 - 15:45, 02.112-128)
  • Exercises to Approximate Computing
    (Übung, Jorge A. Echavarria et al., Di, 10:00 - 12:00, 02.133-128)

Inhalt:

Approximate Computing denotes a quite young research area that exploits the fact and capability of many applications and systems to tolerate imprecision and/or inexactness of computed results. Prominent areas of applications and novel techniques of computing approximate rather than exact results have brought up new implementations either at hardware and/or software levels for important emergent workloads such as searching, mining, image processing, and data retrieval.
Although hardware technology is improving at a fast pace, energy and power are becoming more and more important constraints apart from exactly computing results in an acceptable amount of time. The main goals of approximate computing techniques are therefore to exploit the possible trade-off between power/energy consumption, accuracy, performance, and/or cost, e.g., utilized hardware resources.
The purpose of the course approximate computing is to instruct students about the main ideas and concepts of approximate computing. This includes analyzing the trade-off between energy consumption, accuracy, run-time and hardware costs, concrete approximating techniques (e.g. approximate hardware synthesis, approximating algorithms) as well as theoretical background (determining the computational error and its complexity).

Lernziele und Kompetenzen:

Wissen

• The students know the principles and benefits of Approximate Computing and when it is applicable.

• The students know multiple error metrics and their semantic meaning.

Verstehen

• The students understand the difference between the error metrics.

• The students understand the principle of function falsification.

• The students can apply the presented approximation techniques.

Anwenden

• The students are capable of choosing the appropriate approximation

technique based on given requirements.

Weitere Informationen:

Verwendbarkeit des Moduls / Einpassung in den Musterstudienplan:

1. Advanced Signal Processing & Communications Engineering (Master of Science)
   (Po-Vers. 2020w | TechFak | Advanced Signal Processing & Communications Engineering (Master of Science) | Gesamtkonto | Technical Electives | Approximate Computing)

Studien-/Prüfungsleistungen:

Approximate Computing (Prüfungsnummer: 965820)

(englischer Titel: Approximate Computing)

Prüfungsleistung, mündliche Prüfung, Dauer (in Minuten): 30, benotet, 5 ECTS

Anteil an der Berechnung der Modulnote: 100.0 %

weitere Erläuterungen:
On default, an oral examination of duration 30 minutes will determine your grade. Due to COVID19, the examination can alternatively be held as a remote digital examination using Zoom. However, if a large number of students participate, your grade will be determined by a written examination of duration 60 minutes.

Prüfungssprache: Deutsch oder Englisch

Erstablegung: SS 2021

1. Prüfer:

Oliver Keszöcze,

2. Prüfer:

Jürgen Teich

Termin: 22.07.2021, Ort: 02.112-128, Lehrstuhl CS12, Cauerstraße 11, 91058 Erlangen