INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation Processing

An increasing number of researchers are finding use for nth-order gradient computations for a wide variety of applications, including graphics, meta-learning (MAML), scientific computing, and most recently, implicit neural representations (INRs). Recent work shows that the gradient of an INR can be...

Celý popis

Podrobná bibliografia

Vydané v:	Digest of technical papers - IEEE/ACM International Conference on Computer-Aided Design s. 1 - 9
Hlavní autori:	Abi-Karam, Stefan, Sarkar, Rishov, Xu, Dejia, Fan, Zhiwen, Wang, Zhangyang, Hao, Cong
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 28.10.2023
Predmet:	Adaptation models Computational efficiency Computational modeling Computer architecture Graphics processing units Throughput Transforms
ISSN:	1558-2434
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!