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Direct Cache Access for High Bandwidth Network I/O

Ram Huggahalli, Ravi Iyer, Scott Tetrick
2005 SIGARCH Computer Architecture News  
Analysis of benchmarks such as SPECWeb9, TPC-W and TPC-C shows that overall benefit depends on the relative volume of I/O to memory traffic as well as the spatial and temporal relationship between processor  ...  and I/O memory accesses.  ...  The nature of I/O in the TPC-C benchmark is very different from the other benchmarks that we studied. It is predominantly disk I/O compared to network I/O.  ... 
doi:10.1145/1080695.1069976 fatcat:ocfnimtqgfb6noof7jgz4zrwty

Understanding Scalability and Performance Requirements of I/O-Intensive Applications on Future Multicore Servers

Shoaib Akram, Manolis Marazakis, Angelos Bilas
2012 2012 IEEE 20th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems  
In this paper, we examine the storage I/O behavior of twelve data-centric applications as the number of cores per server grows.  ...  We propose using cycles per I/O (cpio) as a metric for abstracting many I/O subsystem configuration details.  ...  ACKNOWLEDGEMENTS We thankfully acknowledge the support of the European Commission under the 7th Framework Programs through the IOLANES (FP7-ICT-248615), HiPEAC2 (FP7-ICT-217068), and SCALUS (FP7-PEOPLE-ITN  ... 
doi:10.1109/mascots.2012.29 dblp:conf/mascots/AkramMB12 fatcat:rsblms2bqvgcfggtkffqb7sohi

Rethinking main memory OLTP recovery

Nirmesh Malviya, Ariel Weisberg, Samuel Madden, Michael Stonebraker
2014 2014 IEEE 30th International Conference on Data Engineering  
We evaluated our approach on an implementation of TPC C in a main memory database system (VoltDB), and found that command logging can offer 1.5 x higher throughput than a main memory optimized implementation  ...  It then does recovery by starting from a trans actionally consistent checkpoint and replaying the commands in the log as if they were new transactions.  ...  to I/O time.  ... 
doi:10.1109/icde.2014.6816685 dblp:conf/icde/MalviyaWMS14 fatcat:qs272j7u35aapouzdrf5pd5exq

Performance characterization of a Quad Pentium Pro SMP using OLTP workloads

Kimberly Keeton, David A. Patterson, Yong Qiang He, Roger C. Raphael, Walter E. Baker
1998 SIGARCH Computer Architecture News  
To evaluate these issues, we use hardware counters to measure architectural features of a four-processor Pentium Pro-based server running a TPC-C-like workload on an lnformix database.  ...  Commercial applications are an important, yet often overlooked, workload with significantly different characteristics from technical workloads.  ...  Acknowledgments We thank Seckin Unlu of Intel for his help in deciphering the Pentium Pro hardware counters and interpreting experimental results.  ... 
doi:10.1145/279361.279364 fatcat:krdbxhrf5jfvzhi6akmvpxca4q

TraceTracker: Hardware/Software Co-Evaluation for Large-Scale I/O Workload Reconstruction [article]

Miryeong Kwon, Jie Zhang, Gyuyoung Park, Wonil Choi, David Donofrio, John Shalf, Mahmut Kandemir, Myoungsoo Jung
2017 arXiv   pre-print
user scenarios while adjusting them with new system information.  ...  Block traces are widely used for system studies, model verifications, and design analyses in both industry and academia.  ...  Stoica, “Tpc-e vs. tpc-c: Characterizing the new tpc-e is required for each node to ensure data synchronization; the benchmark via an i/o comparison study,” ACM SIGMOD Record, 2011. input data  ... 
arXiv:1709.04806v1 fatcat:ebipkrlzczgdfdpb5qddiv6p3i

Java server benchmarks

S. J. Baylor, M. Devarakonda, S. Fink, E. Gluzberg, M. Kalantar, P. Muttineni, E. Barsness, R. Arora, R. Dimpsey, S. J. Munroe
2000 IBM Systems Journal  
Where applicable, we present benchmarks written using both the Java programming model (i.e., servlets) and the legacy model (i.e., the Common Gateway Interface) for direct comparisons of delivered performance  ...  One obstacle to obtaining this goal has been the lack of well-defined, server-specific, Java benchmarks. This paper helps address this shortcoming by defining representative Java server benchmarks.  ...  Acknowledgments We thank Ben Hoflich, Jimmy Dewitt, and Walter Fraser for helping us to run the benchmarks and graph the results. Cited references  ... 
doi:10.1147/sj.391.0057 fatcat:kvycgojsmzcdljp5xsyazxbeye

Micro-architectural analysis of in-memory OLTP: Revisited

Utku Sirin, Pınar Tözün, Danica Porobic, Ahmad Yasin, Anastasia Ailamaki
2021 The VLDB journal  
As a result, only 30% of the CPU cycles are used to retire instructions, and 70% of the CPU cycles are wasted to stalls for both traditional disk-based and new generation in-memory OLTP.  ...  instruction cache misses or the long-latency data misses from the last-level cache (LLC) are the dominant factors in the overall execution time.  ...  from the copyright holder.  ... 
doi:10.1007/s00778-021-00663-8 fatcat:25dloazt5zaezltqx7jhxnwyfy

Hardware counter driven on-the-fly request signatures

Kai Shen, Ming Zhong, Sandhya Dwarkadas, Chuanpeng Li, Christopher Stewart, Xiao Zhang
2008 SIGARCH Computer Architecture News  
In this paper, we explore the utilization of these statistics as request signatures in server applications for identifying requests and inferring highlevel request properties (e.g., CPU and I/O resource  ...  Our on-the-fly request resource consumption inference (averaging 7%, 3%, 20%, and 41% prediction errors for four server workloads, TPC-C, TPC-H, J2EE-based RUBiS, and a trace-driven index search, respectively  ...  For CPU-bound applications (TPC-C, TPC-H, and RU-BiS), our prediction target is the request CPU usage. For dataintensive index search, our prediction target is the request I/O size.  ... 
doi:10.1145/1353534.1346306 fatcat:ofuzmoeycvhkdiriqijd3ro4z4

Hardware counter driven on-the-fly request signatures

Kai Shen, Ming Zhong, Sandhya Dwarkadas, Chuanpeng Li, Christopher Stewart, Xiao Zhang
2008 ACM SIGOPS Operating Systems Review  
In this paper, we explore the utilization of these statistics as request signatures in server applications for identifying requests and inferring highlevel request properties (e.g., CPU and I/O resource  ...  Our on-the-fly request resource consumption inference (averaging 7%, 3%, 20%, and 41% prediction errors for four server workloads, TPC-C, TPC-H, J2EE-based RUBiS, and a trace-driven index search, respectively  ...  For CPU-bound applications (TPC-C, TPC-H, and RU-BiS), our prediction target is the request CPU usage. For dataintensive index search, our prediction target is the request I/O size.  ... 
doi:10.1145/1353535.1346306 fatcat:3wmyhhxunrhg5c4n7zurxc7tpm

Hardware counter driven on-the-fly request signatures

Kai Shen, Ming Zhong, Sandhya Dwarkadas, Chuanpeng Li, Christopher Stewart, Xiao Zhang
2008 Proceedings of the 13th international conference on Architectural support for programming languages and operating systems - ASPLOS XIII  
In this paper, we explore the utilization of these statistics as request signatures in server applications for identifying requests and inferring highlevel request properties (e.g., CPU and I/O resource  ...  Our on-the-fly request resource consumption inference (averaging 7%, 3%, 20%, and 41% prediction errors for four server workloads, TPC-C, TPC-H, J2EE-based RUBiS, and a trace-driven index search, respectively  ...  For CPU-bound applications (TPC-C, TPC-H, and RU-BiS), our prediction target is the request CPU usage. For dataintensive index search, our prediction target is the request I/O size.  ... 
doi:10.1145/1346281.1346306 dblp:conf/asplos/ShenZDLSZ08 fatcat:6blqfstlvrhdzhjqdksbho2m5a

Hardware counter driven on-the-fly request signatures

Kai Shen, Ming Zhong, Sandhya Dwarkadas, Chuanpeng Li, Christopher Stewart, Xiao Zhang
2008 SIGPLAN notices  
In this paper, we explore the utilization of these statistics as request signatures in server applications for identifying requests and inferring highlevel request properties (e.g., CPU and I/O resource  ...  Our on-the-fly request resource consumption inference (averaging 7%, 3%, 20%, and 41% prediction errors for four server workloads, TPC-C, TPC-H, J2EE-based RUBiS, and a trace-driven index search, respectively  ...  For CPU-bound applications (TPC-C, TPC-H, and RU-BiS), our prediction target is the request CPU usage. For dataintensive index search, our prediction target is the request I/O size.  ... 
doi:10.1145/1353536.1346306 fatcat:kv2oc2v6a5dhng64ujj4lymv7u

Analytical modeling of lock-based concurrency control with arbitrary transaction data access patterns

Pierangelo Di Sanzo, Roberto Palmieri, Bruno Ciciani, Francesco Quaglia, Paolo Romano
2010 Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering - WOSP/SIPEW '10  
The accuracy of our model has been verified against simulation results based on both synthetic data access patterns and patterns derived from the TPC-C benchmark.  ...  In this article we present an accurate analytical model of 2PL concurrency control, which overcomes several limitations of preexisting analytical results.  ...  per second), and where the disk has a fixed I/O delay denoted as t I/O .  ... 
doi:10.1145/1712605.1712619 dblp:conf/wosp/SanzoPCQR10 fatcat:4m4ic436onb5reacj2gmq6bxhy

Performance and resource modeling in highly-concurrent OLTP workloads

Barzan Mozafari, Carlo Curino, Alekh Jindal, Samuel Madden
2013 Proceedings of the 2013 international conference on Management of data - SIGMOD '13  
Resource and performance analysis and prediction-answering questions like "How much disk I/O will my system perform if the requests per second double?"  ...  We have validated these models on MySQL/Linux with numerous experiments on standard benchmarks (TPC-C) and real workloads (Wikipedia), observing very high accuracies (within a few percent error) when predicting  ...  Since the TPC-C benchmark has 9 tables, our dataset consisted of 18 numerical features.  ... 
doi:10.1145/2463676.2467800 dblp:conf/sigmod/MozafariCJM13 fatcat:5vsztx2renetdl22bbm6hqcve4

Characteristics of workloads used in high performance and technical computing

Razvan Cheveresan, Matt Ramsay, Chris Feucht, Ilya Sharapov
2007 Proceedings of the 21st annual international conference on Supercomputing - ICS '07  
Since prefetching plays an important role in the performance of computational workloads, we explore the prefetching potential and for parallel workloads we study the sharing properties of memory accesses  ...  This paper provides a systematic comparison of various characteristics of computationally-intensive workloads. Our analysis focuses on standard HPC benchmarks and representative applications.  ...  ACKNOWLEDGMENTS The authors would like to acknowledge insight, comments and assistance provided by following collegues: Lodewijk  ... 
doi:10.1145/1274971.1274984 dblp:conf/ics/CheveresanRFS07 fatcat:ptpam3kzxzcebp6jm3m3cahlaa

Transaction processing on confidential data using cipherbase

Arvind Arasu, Ken Eguro, Manas Joglekar, Raghav Kaushik, Donald Kossmann, Ravi Ramamurthy
2015 2015 IEEE 31st International Conference on Data Engineering  
Our experiments with TPC-C show that when customer data is strongly encrypted in Cipherbase, it provides 90% the throughput of SQL Server operating over unencrypted data.  ...  Cipherbase is based on a novel architecture that combines an industrial strength database engine (SQL Server) with lightweight processing over encrypted data that is performed in secure hardware.  ...  TPC-C Benchmark Environment We use transactions from the TPC-C benchmark for our evaluation.  ... 
doi:10.1109/icde.2015.7113304 dblp:conf/icde/ArasuEJKKR15 fatcat:maw45dh4kvhjxhrgkaqm4zto6i
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