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ORCIDJacob Nelson 0001
Person information
- affiliation: Microsoft Research, Redmond, WA, USA
- affiliation (Ph.D., 2014): University of Washington, Seattle, WA, USA
Other persons with the same name
- Jacob Nelson-Slivon
![[0009-0006-1968-8863]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0009-0006-1968-8863")
(aka: Jacob Nelson 0002) — Google, USA (and 1 more) - Jacob Nelson 0003 — Tennessee Tech University, Cookeville, TN, USA
- Jacob Nelson 0004 — Appirits Inc., Tokyo, Japan
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2020 – today
- 2023
[c27]Ziyuan Liu, Zhixiong Niu, Ran Shu, Liang Gao, Guohong Lai, Na Wang, Zongying He, Jacob Nelson, Dan R. K. Ports, Lihua Yuan, Peng Cheng, Yongqiang Xiong:
SlimeMold: Hardware Load Balancer at Scale in Datacenter. APNet 2023: 136-142- [c26]Yifan Yuan, Jinghan Huang, Yan Sun, Tianchen Wang, Jacob Nelson, Dan R. K. Ports, Yipeng Wang, Ren Wang, Charlie Tai, Nam Sung Kim:
Rambda: RDMA-driven Acceleration Framework for Memory-intensive µs-scale Datacenter Applications. HPCA 2023: 499-515 - [c25]Aashaka Shah, Vijay Chidambaram, Meghan Cowan, Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Jacob Nelson, Olli Saarikivi:
TACCL: Guiding Collective Algorithm Synthesis using Communication Sketches. NSDI 2023: 593-612 - [i9]Pratyush Patel, Katie Lim, Kushal Jhunjhunwalla, Ashlie Martinez, Max Demoulin, Jacob Nelson, Irene Zhang, Thomas E. Anderson:
Hybrid Computing for Interactive Datacenter Applications. CoRR abs/2304.04488 (2023) - 2022
- [c24]Ziyuan Liu, Zhixiong Niu, Ran Shu, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Lihua Yuan, Jacob Nelson, Dan R. K. Ports:
A Disaggregate Data Collecting Approach for Loss-Tolerant Applications. APNet 2022: 57-62 - [c23]Lior Zeno, Dan R. K. Ports, Jacob Nelson, Daehyeok Kim, Shir Landau Feibish, Idit Keidar, Arik Rinberg, Alon Rashelbach, Igor Lima de Paula, Mark Silberstein:
SwiSh: Distributed Shared State Abstractions for Programmable Switches. NSDI 2022: 171-191 - [c22]Yifan Yuan, Omar Alama, Jiawei Fei, Jacob Nelson, Dan R. K. Ports, Amedeo Sapio, Marco Canini, Nam Sung Kim:
Unlocking the Power of Inline Floating-Point Operations on Programmable Switches. NSDI 2022: 683-700 - [i8]Yifan Yuan, Jinghan Huang, Yan Sun, Tianchen Wang, Jacob Nelson, Dan R. K. Ports, Yipeng Wang, Ren Wang, Charlie Tai, Nam Sung Kim:
ORCA: A Network and Architecture Co-design for Offloading us-scale Datacenter Applications. CoRR abs/2203.08906 (2022) - 2021
- [c21]Amedeo Sapio, Marco Canini, Chen-Yu Ho, Jacob Nelson, Panos Kalnis, Changhoon Kim, Arvind Krishnamurthy, Masoud Moshref, Dan R. K. Ports, Peter Richtárik:
Scaling Distributed Machine Learning with In-Network Aggregation. NSDI 2021: 785-808 - [c20]Zixian Cai, Zhengyang Liu, Saeed Maleki, Madanlal Musuvathi, Todd Mytkowicz, Jacob Nelson, Olli Saarikivi:
Synthesizing optimal collective algorithms. PPoPP 2021: 62-75 - [c19]Daehyeok Kim, Jacob Nelson, Dan R. K. Ports, Vyas Sekar, Srinivasan Seshan:
RedPlane: enabling fault-tolerant stateful in-switch applications. SIGCOMM 2021: 223-244 - [c18]Irene Zhang, Amanda Raybuck, Pratyush Patel, Kirk Olynyk, Jacob Nelson, Omar S. Navarro Leija, Ashlie Martinez, Jing Liu, Anna Kornfeld Simpson, Sujay Jayakar, Pedro Henrique Penna, Max Demoulin, Piali Choudhury, Anirudh Badam:
The Demikernel Datapath OS Architecture for Microsecond-scale Datacenter Systems. SOSP 2021: 195-211 - [c17]Matthew Burke, Sowmya Dharanipragada, Shannon Joyner, Adriana Szekeres, Jacob Nelson, Irene Zhang, Dan R. K. Ports:
PRISM: Rethinking the RDMA Interface for Distributed Systems. SOSP 2021: 228-242 - [c16]Henry N. Schuh, Weihao Liang, Ming Liu, Jacob Nelson, Arvind Krishnamurthy:
Xenic: SmartNIC-Accelerated Distributed Transactions. SOSP 2021: 740-755 - [i7]Liang Luo, Jacob Nelson, Arvind Krishnamurthy, Luis Ceze:
Cloud Collectives: Towards Cloud-aware Collectives forML Workloads with Rank Reordering. CoRR abs/2105.14088 (2021) - [i6]Aashaka Shah, Vijay Chidambaram, Meghan Cowan, Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Jacob Nelson, Olli Saarikivi, Rachee Singh:
Synthesizing Collective Communication Algorithms for Heterogeneous Networks with TACCL. CoRR abs/2111.04867 (2021) - [i5]Yifan Yuan, Omar Alama, Amedeo Sapio, Jiawei Fei, Jacob Nelson, Dan R. K. Ports, Marco Canini, Nam Sung Kim:
Unlocking the Power of Inline Floating-Point Operations on Programmable Switches. CoRR abs/2112.06095 (2021) - 2020
- [c15]Anna Kornfeld Simpson, Adriana Szekeres, Jacob Nelson, Irene Zhang:
Securing RDMA for High-Performance Datacenter Storage Systems. HotCloud 2020 - [c14]Lior Zeno, Dan R. K. Ports, Jacob Nelson, Mark Silberstein:
SwiShmem: Distributed Shared State Abstractions for Programmable Switches. HotNets 2020: 160-167 - [c13]Liang Luo, Peter West, Arvind Krishnamurthy, Luis Ceze, Jacob Nelson:
PLink: Discovering and Exploiting Locality for Accelerated Distributed Training on the public Cloud. MLSys 2020 - [c12]Jialin Li, Jacob Nelson, Ellis Michael, Xin Jin, Dan R. K. Ports:
Pegasus: Tolerating Skewed Workloads in Distributed Storage with In-Network Coherence Directories. OSDI 2020: 387-406 - [i4]Zixian Cai, Zhengyang Liu, Saeed Maleki, Madan Musuvathi, Todd Mytkowicz, Jacob Nelson, Olli Saarikivi:
Synthesizing Optimal Collective Algorithms. CoRR abs/2008.08708 (2020)
2010 – 2019
- 2019
- [c11]Dan R. K. Ports, Jacob Nelson:
When Should The Network Be The Computer? HotOS 2019: 209-215 - [i3]Amedeo Sapio, Marco Canini, Chen-Yu Ho, Jacob Nelson, Panos Kalnis, Changhoon Kim, Arvind Krishnamurthy, Masoud Moshref, Dan R. K. Ports, Peter Richtárik:
Scaling Distributed Machine Learning with In-Network Aggregation. CoRR abs/1903.06701 (2019) - 2018
- [c10]Liang Luo, Jacob Nelson, Luis Ceze, Amar Phanishayee, Arvind Krishnamurthy:
Parameter Hub: a Rack-Scale Parameter Server for Distributed Deep Neural Network Training. SoCC 2018: 41-54 - [i2]Liang Luo, Jacob Nelson, Luis Ceze, Amar Phanishayee, Arvind Krishnamurthy:
Parameter Hub: High Performance Parameter Servers for Efficient Distributed Deep Neural Network Training. CoRR abs/1801.09805 (2018) - [i1]Liang Luo, Jacob Nelson, Luis Ceze, Amar Phanishayee, Arvind Krishnamurthy:
Parameter Hub: a Rack-Scale Parameter Server for Distributed Deep Neural Network Training. CoRR abs/1805.07891 (2018) - 2017
- [c9]Ming Liu, Liang Luo, Jacob Nelson, Luis Ceze, Arvind Krishnamurthy, Kishore Atreya:
IncBricks: Toward In-Network Computation with an In-Network Cache. ASPLOS 2017: 795-809 - [c8]Naveen Kr. Sharma, Antoine Kaufmann, Thomas E. Anderson, Arvind Krishnamurthy, Jacob Nelson, Simon Peter:
Evaluating the Power of Flexible Packet Processing for Network Resource Allocation. NSDI 2017: 67-82 - 2016
- [c7]Rob F. Van der Wijngaart, Abdullah Kayi, Jeff R. Hammond, Gabriele Jost, Tom St. John, Srinivas Sridharan, Timothy G. Mattson, John Abercrombie, Jacob Nelson:
Comparing Runtime Systems with Exascale Ambitions Using the Parallel Research Kernels. ISC 2016: 321-339 - 2015
- [j2]Jacob Nelson, Brandon Holt, Brandon Myers, Preston Briggs, Simon Kahan, Luis Ceze, Mark Oskin:
Trading Latency for Performance in Data-Intensive Applications. login Usenix Mag. 40(5) (2015) - [c6]Golnoosh Farnadi, Zeinab Mahdavifar, Ivan Keller, Jacob Nelson, Ankur Teredesai, Marie-Francine Moens, Martine De Cock:
Scalable adaptive label propagation in Grappa. IEEE BigData 2015: 1485-1491 - [c5]Thierry Moreau, Mark Wyse, Jacob Nelson, Adrian Sampson, Hadi Esmaeilzadeh, Luis Ceze, Mark Oskin:
SNNAP: Approximate computing on programmable SoCs via neural acceleration. HPCA 2015: 603-614 - [c4]Jacob Nelson, Brandon Holt, Brandon Myers, Preston Briggs, Luis Ceze, Simon Kahan, Mark Oskin:
Latency-Tolerant Software Distributed Shared Memory. USENIX Annual Technical Conference 2015: 291-305 - 2014
- [b1]Jacob Nelson:
Latency-Tolerant Distributed Shared Memory For Data-Intensive Applications. University of Washington, USA, 2014 - [j1]Adrian Sampson, Jacob Nelson, Karin Strauss, Luis Ceze:
Approximate Storage in Solid-State Memories. ACM Trans. Comput. Syst. 32(3): 9:1-9:23 (2014) - 2013
- [c3]Adrian Sampson, Jacob Nelson, Karin Strauss, Luis Ceze:
Approximate storage in solid-state memories. MICRO 2013: 25-36 - 2011
- [c2]Joseph Devietti, Jacob Nelson, Tom Bergan, Luis Ceze, Dan Grossman:
RCDC: a relaxed consistency deterministic computer. ASPLOS 2011: 67-78 - [c1]Jacob Nelson, Brandon Myers, A. H. Hunter, Preston Briggs, Luis Ceze, Carl Ebeling, Dan Grossman, Simon Kahan, Mark Oskin:
Crunching Large Graphs with Commodity Processors. HotPar 2011
Coauthor Index
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