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ISTC-CC NEWSLETTER
RESEARCH HIGHLIGHTS
Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
ISTC-CC provides a listing of useful benchmarks for cloud computing.
Another list highlighting Open Source Software Releases.
Second GraphLab workshop should be even bigger than the first! GraphLab is a new programming framework for graph-style data analytics.
ISTC-CC 2014 Retreat: Posters
PipeCheck: Verifying Consistency Model Implementations
Daniel Lustig (Princeton), Caroline Trippel (Princeton), Michael Pellauer (Intel VSSAD), and Margaret Martonosi (Princeton)
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SpringFS: Bridging Agility and Performance in Elastic Distributed Storage
Lianghong Xu, James Cipar, Elie Krevat, Alexey Tumanov, Nitin Gupta, Michael A. Kozuch*, Greg Ganger (CMU, *Intel Labs)
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Flipping Bits in Memory Without Accessing Them
Yoongu Kim (CMU), Ross Daly, Jeremie Kim (CMU), Chris Fallin, Ji Hye Lee (CMU), Donghyuk Lee (CMU), Chris Wilkerson (Intel Labs), Konrad Lai, Onur Mutlu (CMU)
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The Efficacy of Error Mitigation Techniques for DRAM Retention Failures: A Comparative Experimental Study
Samira Khan (CMU/Intel Labs), Donghyuk Lee (CMU), Yoongu Kim (CMU), Alaa Alameldeen (Intel Labs), Chris Wilkerson (Intel Labs), and Onur Mutlu (CMU)
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Algorithmic Improvements for Fast Concurrent Cuckoo Hashing
Xiaozhou Li (Princeton), David G. Andersen (CMU), Michael Kaminsky (Intel Labs), Michael J. Freedman (Princeton)
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Shader-Assisted Dynamic Bottleneck Mitigation in GPUs
Nandita Vijaykumar(CMU), Gennady Pekhimenko(CMU), Abhishek Bhowmick (CMU), Adwait Jog(CMU), Onur Mutlu(CMU), Todd C Mowry (CMU)
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The Dirty-Block Index
Vivek Seshadri, Abhishek Bhowmick, Onur Mutlu, Phillip B. Gibbons, Michael A. Kozuch*, Todd C. Mowry (CMU, *Intel Labs)
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RowClone: Fast and Energy-efficient In-DRAM Bulk Data Copy and Initialization
Vivek Seshadri, Yoongu Kim, Chris Fallin, Donghyuk Lee, Rachata Ausavarungnirun, Gennady Pekhimenko, Yixin Luo, Onur Mutlu, Phillip B. Gibbons*, Michael A. Kozuch*, Todd C. Mowry (CMU, *Intel Labs)
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LazyTable: Distributed Machine Learning with the Stale Synchronous Parallel Model
Qirong Ho, Henggang Cui, James Cipar, Jin Kyu Kim, Abhimanu Kumar, Seunghak Lee, Wei Dai, Jinliang Wei, Greg Ganger, Phil Gibbons*, Garth Gibson, Eric Xing (CMU, *Intel Labs)
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Exploiting Iterative-ness for Parallel ML Computations
Henggang Cui, Alexey Tumanov, Jinliang Wei, Lianghong Xu, Wei Dai, Jesse Haber-Kucharsky, Qirong Ho, Gregory R. Ganger, Phil B. Gibbons*, Garth A. Gibson, Eric P. Xing (CMU, *Intel)
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Exploiting Bounded Staleness To Speed Up Big Data Analytics
Henggang Cui, James Cipar, Qirong Ho, Jin Kyu Kim, Abhimanu Kumar, Seunghak Lee, Wei Dai, Jinliang Wei, Greg Ganger, Phil Gibbons*, Garth Gibson, Eric Xing (CMU, *Intel)
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MICA: A Holistic Approach to Fast In-Memory Key-Value Storage
Hyeontaek Lim (CMU), Dongsu Han (KAIST), David G. Andersen (CMU), Michael Kaminsky (Intel Labs)
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Cloudlet-based Wearable Cognitive Assistance
Mahadev Satyanarayanan (PI), Martial Hebert (co-PI), Dan Siewiorek (co-PI), Yoshihisa Abe, Zhuo Chen, Da-Yoon Chung, Benjamin Gilbert, Kiryong Ha, Jan Harkes Wenlu Hu, Ishan Misra, Padmanabhan Pillai*, Wolfgang Richter, Brandon Taylor (CMU, *Intel Labs)
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Linearly Compressed Pages: A Low Complexity, Low Latency Main Memory Compression Framework
Gennady Pekhimenko, Vivek Seshadri, Yoongu Kim, Hongyi Xin, Onur Mutlu, Todd C. Mowry, Phillip B. Gibbons*, Michael A. Kozuch* (CMU, *Intel Labs)
PDF
Tetrisched: Space-Time Scheduling for Heterogeneous Datacenters
Alexey Tumanov (CMU), Timothy Zhu (CMU), Michael A. Kozuch (Intel Labs), Mor Harchol-Balter (CMU), Greg Ganger (CMU)
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Using RDMA Efficiently for Key-Value Services
Anuj Kalia (CMU), Michael Kaminsky (Intel Labs), David G. Andersen (CMU)
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Characterizing Application Memory Error Vulnerability to Optimize Datacenter Cost via Heterogeneous-Reliability Memory
Yixin Luo, Sriram Govindan*, Bikash Sharma*, Mark Santaniello*, Justin Meza, Aman Kansal*, Jie Liu*, Badriddine Khessib*, Kushagra Vaid*, Onur Mutlu (CMU, *Microsoft Corporation)
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Improving DRAM Performance by Parallelizing Refreshes with Accesses
Kevin Chang, Donghyuk Lee, Zeshan Chisti*, Alaa Alameldeen*, Chris Wilkerson*, Yoongu Kim, Onur Mutlu (CMU, *Intel Labs)
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The Power of Choice in Data-Aware Cluster Scheduling
Shivaram Venkataraman, Aurojit Panda, Ganesh Ananthanarayanan*, Michael J. Franklin, Ion Stoica (UC Berkeley, *Microsoft Research)
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Efficient Lightweight Fast Stream Processing at Scale
Liting Hu, Karsten Schwan, Hrishikesh Amur, Xin Chen (Georgia Tech)
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PriorityMeister: Tail Latency QoS for Shared Networked Storage
Timothy Zhu, Alexey Tumanov, Michael A. Kozuch*, Mor Harchol-Balter, Greg Ganger (CMU, *Intel Labs)
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Optimizing Relational Computing Performance on Heterogeneous Processors
H. Wu, I. Saeed, J. Young, and S. Yalamanchili (Georgia Tech)
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Pruning Masstree
Huanchen Zhang, David G. Andersen, Michael Kaminsky* (CMU, *Intel Labs)
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Let's Squeeze Memory out of Index Structures
Huanchen Zhang, Andrew Pavlo, David G. Andersen, Michael Kaminsky*
(CMU, *Intel Labs)
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Managed Communication for Fast Large-Scale Iterative Analytics
Jinliang Wei, Wei Dai, Henggang Cui, Qirong Ho, Greg Ganger, Phil Gibbons*, Garth Gibson, Eric Xing (CMU, *Intel Labs)
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Scaling Distributed File System Metadata Throughput using IndexFS
Kai Ren, Qing Zheng, Swapnil Patil, Garth Gibson (CMU)
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Forwarding Table Scalability For Cluster Switches
Dong Zhou, Bin Fan, Hyeontaek Lim, David G. Andersen, Michael Kaminsky*, Michael Mitzenmacher†(CMU, *Intel Labs, †Harvard)
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Scalable, High Performance Ethernet Forwarding with CuckooSwitch
Dong Zhou, Bin Fan, Hyeontaek Lim, Michael Kaminsky*, David G. Andersen (CMU, *Intel Labs)
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Scaling Queries over Big RDF Graphs with Semantic Hash Partitioning
Kisung Lee, Ling Liu (Georgia Tech)
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GraphLens: Mining Enterprise Storage Workloads Using Graph Analytics
Yang Zhou, Sangeetha Seshadri, Lawrence Chiu, Ling Liu (Georgia Tech, IBM Almaden Research Center)
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Tachyon: A Reliable Memory Centric Storage for Big Data
Haoyuan Li, Ali Ghodsi, Matei Zaharia, Scott Shenker, Ion Stoica
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STRADS: Parallel ML Scheduling for High Efficiency
Jin Kyu Kim, Seunghak Lee, Eric Xing, Garth Gibson (CMU)
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Ligra++: Processing Large Graphs Using Compression
Julian Shun, Laxman Dhulipala, Guy Blelloch (CMU)
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PETUUM: An ML-Centric System for Big Learning
Wei Dai, Jinliang Wei, Jin Kyu Kim, Qirong Ho, Xun Zheng, Pengtao Xie, Eric Xing (CMU)
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Scaling Feature Selection with Aggressive Subsets
Tyler B. Johnson, Carlos Guestrin (University of Washington)
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Scaling Machine Learning with the Parameter Server
Mu Li, Dave Andersen, Li Zhou, Junwoo Park, Alex Smola, Amr Ahmed*, Vanja Josifovski*, Bor-Yiing Su*, Eugene Shekita* (CMU, *Google)
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GraphX: Unified Data-Parallel and Graph-Parallel Analytics
Joseph Gonzalez, Reynold Xin, Ankur Dave, Dan Crankshaw, Mike Franklin, Ion Stoica (UC Berkeley)
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Intel ONP for Servers -- Opening the Doors to SND/NfV
Joseph Gasparakis (Intel)
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