Data-oriented design: Difference between revisions

Revision as of 17:13, 2 December 2023

Revision as of 17:23, 2 December 2023

Line 14:

== Contrast with object orientation ==

{{Original research section|date=September 2021}}

The claim is that traditional [[object-oriented programming]] (OOP) design principles result in poor data locality <ref>{{cite web

The claim is that traditional [[object-oriented programming]] (OOP) design principles result in poor data locality <ref>https://www.intel.com/content/dam/www/public/us/en/documents/presentation/improving-vectorization-efficiency.pdf</ref><ref>https://arxiv.org/pdf/1710.03462.pdf</ref>, more so if runtime polymorphism ([[dynamic dispatch]]) is used (which is especially problematic on some processors).<ref>{{cite web|title=What's wrong with Object-Oriented Design? Where's the harm in it?|url=http://www.dataorienteddesign.com/dodmain/node17.html}}describes the problems with virtual function calls, e.g., i-cache misses</ref><ref>{{cite web|title=Data-oriented design - why you might be shooting yourself in the foot with OOP|url=http://gamesfromwithin.com/data-oriented-design}}</ref> Although OOP appears to "organise code around data", it actually organises [[source code]] around [[data type]]s rather than physically grouping individual fields and arrays in an efficient format for access by specific functions. Moreover, it often hides layout details under [[abstraction layer]]s, while a data-oriented programmer wants to consider this first and foremost.

| title = INTEL ® HPC DEVELOPER CONFERENCE FUEL YOUR INSIGHT IMPROVE VECTORIZATION EFFICIENCY USING INTEL SIMD DATA LAYOUT TEMPLATE (INTEL SDLT),

| url = https://www.intel.com/content/dam/www/public/us/en/documents/presentation/improving-vectorization-efficiency.pdf

}}</ref><ref>{{cite journal

| title = SoAx: A generic C++ Structure of Arrays for handling particles in HPC codes

| url = https://arxiv.org/pdf/1710.03462.pdf

| author1 = Holger Homann

| author2 = Francois Laenen

| journal = Computer Physics Communications

| arxiv = 1710.03462

| language = English

The claim is that traditional [[object-oriented programming]] (OOP) design principles result in poor data locality <ref>https://www.intel.com/content/dam/www/public/us/en/documents/presentation/improving-vectorization-efficiency.pdf</ref><ref>https://arxiv.org/pdf/1710.03462.pdf}}</ref>, more so if runtime polymorphism ([[dynamic dispatch]]) is used (which is especially problematic on some processors).<ref>{{cite web|title=What's wrong with Object-Oriented Design? Where's the harm in it?|url=http://www.dataorienteddesign.com/dodmain/node17.html}}describes the problems with virtual function calls, e.g., i-cache misses</ref><ref>{{cite web|title=Data-oriented design - why you might be shooting yourself in the foot with OOP|url=http://gamesfromwithin.com/data-oriented-design}}</ref> Although OOP appears to "organise code around data", it actually organises [[source code]] around [[data type]]s rather than physically grouping individual fields and arrays in an efficient format for access by specific functions. Moreover, it often hides layout details under [[abstraction layer]]s, while a data-oriented programmer wants to consider this first and foremost.

== See also ==