Performance characterization of a Quad Pentium Pro SMP using OLTP workloads

Keeton, Kimberly; Patterson, David A.; He, Yong Qiang; Raphael, Roger C.; Baker, Walter E.

doi:10.1145/279361.279364

Cited by 44 publications

(56 citation statements)

References 16 publications

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“…Other studies of database workloads indicate that OLTP (online transaction processing) workloads are characterized by a large memory footprint, combined with a small critical working set [447], and by the reduced benefit from microarchitectural optimizations [397]. In addition, index searching in OLTP workloads requires a different cache design [60].…”

Section: Database Systemsmentioning

confidence: 99%

Workload Modeling for Computer Systems Performance Evaluation

Feitelson

2015

196

131

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Reliable performance evaluations require the use of representative workloads. This is no easy task since modern computer systems and their workloads are complex, with many interrelated attributes and complicated structures. Experts often use sophisticated mathematics to analyze and describe workload models, making these models difficult for practitioners to grasp. This book aims to close this gap by emphasizing the intuition and the reasoning behind the definitions and derivations related to the workload models. It provides numerous examples from real production systems, with hundreds of graphs. Using this book, readers will be able to analyze collected workload data and clean it if necessary, derive statistical models that include skewed marginal distributions and correlations, and consider the need for generative models and feedback from the system. The descriptive statistics techniques covered are also useful for other domains.

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Section: Database Systemsmentioning

confidence: 99%

Workload Modeling for Computer Systems Performance Evaluation

Feitelson

2015

196

131

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“…-If a and b are placed far apart from one another and different threads perform both read and write accesses to their fields, then due to the cache coherency protocol (Keeton et al 1998) the different threads would invalidate the cache lines. Accessing a and then b will cause two cache misses and with it two BusRd/BusRdx events in higher probability.…”

Section: Experimenting With the Oi Refactoring Processmentioning

confidence: 99%

Refactoring techniques for aggressive object inlining in Java applications

et al. 2011

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Object Inlining (OI) is a known optimization in object oriented programming in which referenced objects of class B are inlined into their referencing objects of class A by making all fields and methods of class B part of class A. The optimization saves all the new operations of B type objects from class A and at the same time replaces all indirect accesses, from A to fields of B, by direct accesses. To the best of our knowledge, in-spite of the significant performance potential of the OI optimization, reported performance measurements were relatively moderate. This is because an aggressive OI optimization requires complex analysis and code transformations to overcome problems like multiple references to the inlinable object, object references that escape their object scope, etc.To extract the full potential of OI, we propose a two-stage process. The first stage includes automatic analysis of the source code that informs the user, via comments in the IDE, about code transformations that are needed in order to enable or to maximize the potential of the OI optimization. In the second stage, the OI optimization is applied automatically on the source code as a code refactoring operation, or preferably, as part of the compilation process prior to javac run.We show that this half-automated technique helps to extract the full potential of OI. The proposed OI refactoring process also determines the order of applying the inlinings of the objects and enables us to apply inlinings of objects created inside a method; thus enabling us to reach better performance gain.In this work we also include an evaluation of the OI optimization effects on multithreaded applications running on multicore machines.The comments and the OI transformation were implemented in the Eclipse JDT (Java Development Tools) plugin. The system was then applied on the SPECjbb2000 source code along with profiling data collected by the Eclipse TPTP plugin. The proposed system achieved 46% improvement in performance.

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“…Therefore, re-evaluating the DBMS's performance is significant to both the computer architecture and database communities. Previous studies have shown that DBMS exhibits high cache miss rates and low CPU utilization [1]. Simultaneous Multithreading (SMT) [2] is a form of hardware multithreading, where a single physical multithreaded processor can execute multiple threads concurrently.…”

Section: Introductionmentioning

confidence: 99%

“…In this implementation a thread is created for each client's transaction. 1 The intuition is to improve performance by utilizing the underlying thread mechanism provided by the operating system. This is further improved by using symmetric multi-processors (SMP) architectures.…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Effects of Hyperthreading on the Performance of Data Management Systems

Hassanein

Rashid

Hammad

2008

Int J Parallel Prog

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As information processing applications take greater roles in our everyday life, database management systems (DBMSs) are growing in importance. DBMSs have traditionally exhibited poor cache performance and large memory footprints, therefore performing only at a fraction of their ideal execution and exhibiting low processor utilization. Previous research has studied the memory system of DBMSs on researchbased simultaneous multithreading (SMT) processors. Recently, several differences have been noted between the real hyper-threaded architecture implemented by the Intel Pentium 4 and the earlier SMT research architectures. This paper characterizes the performance of a prototype open-source DBMS running TPC-equivalent benchmark queries on an Intel Pentium 4 Hyper-Threading processor. We use hardware counters provided by the Pentium 4 to evaluate the micro-architecture and study the memory system behavior of each query running on the DBMS. Our results show a performance improvement of up to 1.16 in TPC-C-equivalent and 1.26 in TPC-H-equivalent queries due to hyperthreading.

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Performance characterization of a Quad Pentium Pro SMP using OLTP workloads

Abstract: Commercial applications are an important, yet often overlooked, workload with significantly different characteristics from technical workloads. The potential impact of these differences is that computers optimized for technical workloads may not

Cited by 44 publications

References 16 publications

Workload Modeling for Computer Systems Performance Evaluation

Workload Modeling for Computer Systems Performance Evaluation

Refactoring techniques for aggressive object inlining in Java applications

Analyzing the Effects of Hyperthreading on the Performance of Data Management Systems

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