Biscuit: A Framework for Near-Data Processing of Big Data Workloads
By Bon-Geun Gu, A. Yoon, Duck-Ho Bae, Insoon Jo, Jinyoung Lee, Jonghyun Yoon, Jeong-Uk Kang, Moonsang Kwon, Chanho Yoon, Sangyeun Cho and 2 more. International Symposium on Computer Architecture, 2016
309 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/f96efbad191c388706ce370dd9be5d2c25a7b3dc
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Saugata Ghose
- Rachata Ausavarungnirun
- Juan Gómez-Luna
- Onur Mutlu
- Carole-Jean Wu
- Udit Gupta
- Gu-Yeon Wei
- David M. Brooks
In Information Systems
- Carole-Jean Wu
- Saugata Ghose
- Caroline Trippel
- Rachata Ausavarungnirun
- Juan Gómez-Luna
- Onur Mutlu
- David M. Brooks
- Gu-Yeon Wei
Citations in the corpus
- Processing Data Where It Makes Sense: Enabling In-Memory Computation (2019, background): “The second approach takes advantage of the design of emerging 3D-stacked memory technologies to enable PIM in a more general-purpose manner [7, 34, 35, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 70, 72, 73, 74, 75, 77, 87, 88, 89, 91].”
- RecSSD: near data processing for solid state drive based recommendation inference (2021, methodology): “Leveraging this compute capability, there has been much work on both software and hardware solutions for Near Data Processing in SSDs for other datacenter applications [14, 18, 25, 31, 35, 36, 38, 39].”
- DeepStore: In-Storage Acceleration for Intelligent Queries (2019, background): “In-storage Computing: There have been several works exploring near-storage or in-storage processing for applications such as database query processing [38, 39, 63, 64, 81], key-value store [81], mapreduce workloads [45, 63], signal processing [19], and data analysis [87, 88].”
- RowHammer: A Retrospective (2019, unknown): “, [13]–[15], [18], [22], [24], [34]–[36], [56], [63], [72], [77], [78], [80], [91], [92], [95], [96], [99], [101], [102], [111], [121]–[123], [151], [153], [154], [160], [161], [172], [178], [179], [182], [195], [198], [215]–[219], [221], [222], [228], [257], and [260]).”