Store Mi phone M

advertisement


Store
Devices Microsoft Surface PCs & tablets Xbox Virtual reality Accessories Windows
phone Microsoft Band Software Office Windows Additional software Apps All apps
Windows apps Windows phone apps Games Xbox One games Xbox 360 games PC
games Windows games Windows phone games Entertainment All Entertainment
Movies & TV Music Business & Education Business Store Education Store Developer
Sale Back-to-school essentials Sale Products
Software & services Windows Office Free downloads & security Internet Explorer
Microsoft Edge Skype OneNote OneDrive Microsoft Health MSN Bing Microsoft
Groove Microsoft Movies & TV Devices & Xbox All Microsoft devices Microsoft
Surface All Windows PCs & tablets PC accessories Xbox & games Microsoft Band
Microsoft Lumia All Windows phones Microsoft HoloLens For business Cloud
Platform Microsoft Azure Microsoft Dynamics Windows for business Office for
business Skype for business Surface for business Enterprise solutions Small business
solutions Find a solutions provider Volume Licensing For developers & IT pros
Develop Windows apps Microsoft Azure MSDN TechNet Visual Studio For students
& educators Office for students OneNote in classroom Shop PCs & tablets perfect
for students Microsoft in Education Support
Sign in


Research Research
o Research Home
o Research areas
 Algorithms
 Artificial intelligence and machine learning
 Computer systems and networking
 Computer vision
 Data visualization, analytics, and platform
 Ecology and environment
 Economics
 Graphics and multimedia
 Hardware, devices, and quantum computing
 Human-centered computing
 Mathematics







o
o
o
o
o



Medical, health, and genomics
Natural language processing and speech
Programming languages and software engineering
Search and information retrieval
Security, privacy, and cryptography
Social Sciences
Technology for emerging markets
Products & Downloads
Programs & Events
 Academic Programs
 Events & Conferences
People
Careers
About
 About
 Microsoft Research blog
 Asia Lab
 Cambridge Lab
 India Lab
 New England Lab
 New York City Lab
 Redmond Lab
 Applied Sciences Lab
Research areas
o Algorithms
o Artificial intelligence and machine learning
o Computer systems and networking
o Computer vision
o Data visualization, analytics, and platform
o Ecology and environment
o Economics
o Graphics and multimedia
o Hardware, devices, and quantum computing
o Human-centered computing
o Mathematics
o Medical, health, and genomics
o Natural language processing and speech
o Programming languages and software engineering
o Search and information retrieval
o Security, privacy, and cryptography
o Social Sciences
o Technology for emerging markets
Products & Downloads
Programs & Events
o Academic Programs
o



Events & Conferences
People
Careers
About
o About
o Microsoft Research blog
o Asia Lab
o Cambridge Lab
o India Lab
o New England Lab
o New York City Lab
o Redmond Lab
o Applied Sciences Lab
Code Generation and Factoring for Fast
Evaluation of Low-order Spherical
Harmonic Products and Squares
May 1, 2006

Download Document

BibTex
Authors

John Snyder
Publication Type
TechReport
Pages
9
Number
MSR-TR-2006-53

Abstract

Related Info
Abstract
We present a method for fast evaluation of spherical harmonic (SH) products or, more generally,
any binary product of vectors yielding a vector, where the product is governed by a fixed, sparse,
symmetric, order 3 tensor, denoted Γijk. The method is given the nonzero entries of Γ as input
(they can be computed analytically or by numerical integration for the SH basis) and makes use
of an offline code generator to perform the necessary array indexing using constants rather than
variables. Factoring is performed by collecting the tensor’s nonzero components, represented
by index triples (i,j,k), into groups (i,j,k1), (i,j,k2), …,(i,j,kNij) which share a common pair of
indices (i,j) in the triple, and which vary only in the third (completion) index km and its
corresponding coefficient dm = Γijkm where m ∈ \1,2,…,Nij$. The collection is done using a
greedy method that successively chooses the index pair (i,j) maximizing the number Nij of
different km needed to complete the tensor’s nonzero index triples. The greedy method then
continues to the next best initial pair, generates its contribution, and so on, until all nonzero
triples have been accounted for. The combination of “greedy pair― factoring and
generating constant array indices produces code that is significantly faster than naïve
evaluation methods.
Related Info
Research Areas
 Mathematics
Research Labs
 Microsoft Research Lab - Redmond
Follow Microsoft Research


Follow @MSFTResearch

Share this page


Tweet

Learn

Windows

Office

Skype

Outlook

OneDrive

MSN
Devices

Microsoft Surface

Xbox

PC and laptops

Microsoft Lumia

Microsoft Band

Microsoft HoloLens
Microsoft Store

View account

Order tracking

Retail store locations

Returns

Sales & support
Downloads

Download Center

Windows downloads

Windows 10 Apps

Office Apps

Microsoft Lumia Apps

Internet Explorer
Values

Diversity and inclusion

Accessibility

Environment

Microsoft Philanthropies

Corporate Social Responsibility

Privacy at Microsoft
Company

Careers

About Microsoft

Company news

Investors

Research

Site map

English (United States)

Contact us

Privacy & cookies

Terms of use

Trademarks

About our ads

© 2016 Microsoft
​
Download