A performance methodology for commercial servers

Kunkel, S.; Eickemeyer, Richard J.; Lipasti, Mikko H.; Mullins, Tim; O'Krafka, B.; Rosenberg, Harold A.; VanderWiel, S. P.; Vitale, Philip L.; Whitley, L. D.

doi:10.1147/rd.446.0851

Cited by 42 publications

(19 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The CPI numbers were compared against a detailed production-quality performance simulator used in IBM [21]. On average for all 12 benchmarks SLATE results were within 16% of the production simulator results, which is acceptable for an early analysis system.…”

Section: A Core Modelmentioning

confidence: 90%

Exploring power management in multi-core systems

Bergamaschi¹,

Han²,

Buyuktosunoglu³

et al. 2008

2008 Asia and South Pacific Design Automation Conference

View full text Add to dashboard Cite

Power dissipation has become a critical design metric in microprocessor-based system design. In a multi-core system, running multiple applications, power and performance can be dynamically traded off using an integrated power management (PM) unit. This PM unit monitors the performance and power of each core and dynamically adjusts the individual voltages and frequencies in order to maximize system performance under a given power budget (usually set by the operating system). This paper presents a performance and power analysis methodology, featuring a simulation model for multi-core systems that can be easily reconfigured for different scenarios and a PM infrastructure for the exploration and analysis of PM algorithms. Two algorithms have been implemented: one for discrete and one for continuous power modes based on non-linear programming. Extensive experiments are reported, illustrating the effect of power management both at the core and the chip level.

show abstract

Section: A Core Modelmentioning

confidence: 90%

Exploring power management in multi-core systems

Bergamaschi¹,

Han²,

Buyuktosunoglu³

et al. 2008

2008 Asia and South Pacific Design Automation Conference

View full text Add to dashboard Cite

show abstract

“…For performance modeling, we use a combination of detailed functional simulation and queuing simulation tools [21]. The functional simulator is used for modeling the memory subsystem as well as the interconnection between modules.…”

Section: Modeling Multi-core Architecturesmentioning

confidence: 99%

“…All our performance evaluations have been done using commercial workloads, including TPC-C, TPC-W, TPC-H, Notesbench and others further described in [21]. The server workloads used represent such market segments as on-line transaction processing (OLTP), business intelligence, enterprise resource planning, web serving, and collaborative groupware.…”

Section: Workloadmentioning

confidence: 99%

“…We use PowerPC instruction and data reference traces of the workloads running under AIX. The traces are taken in a nonintrusive manner by attaching a hardware monitor to a processor [9,21]. This enables the traces to be gathered while the system is fully loaded with the normal number of users, and captures the full effects of multitasking, data sharing, interrupts, etc.…”

Section: Workloadmentioning

confidence: 99%

See 1 more Smart Citation

Interconnections in Multi-Core Architectures: Understanding Mechanisms, Overheads and Scaling

Kumar

Zyuban

Tullsen

32nd International Symposium on Computer Architecture (ISCA'05)

242

168

View full text Add to dashboard Cite

show abstract

“…Kunkel et al described a general methodology for analyzing the performance of servers running commercial workloads [13]. Jann et al compared the architecture and OS-level characteristics of Trade6 on two different IBM pSeries servers with the aim of finding bottlenecks and possible improvements in the OS [12].…”

Section: Related Workmentioning

confidence: 99%

Workload characterization of selected JEE-based Web 2.0 applications

Nagpurkar

Horn

Gopalakrishnan

et al. 2008

2008 IEEE International Symposium on Workload Characterization

View full text Add to dashboard Cite

Web 2.0 represents the evolution of the web from a source of information to a platform. Network advances have permitted users to migrate from desktop applications to so-called Rich Internet Applications (RIAs) characterized by thin clients, which are browser-based and store their state on managed servers. Other Web 2.0 technologies have enabled users to more easily participate, collaborate, and share in web-based communities. With the emergence of wikis, blogs, and social networking, users are no longer only consumers, they become contributors to the collective knowledge accessible on the web. In another Web 2.0 development, content aggregation is moving from portal-based technologies to more sophisticated socalled mashups where aggregation capabilities are greatly expanded.While Web 2.0 has generated a great deal of interest and discussion, there has not been much work on analyzing these emerging workloads. This paper presents a detailed characterization of several applications that exploit Web 2.0 technologies, running on an IBM Power5 system, with the goal of establishing, whether the server-side workloads generated by Web 2.0 applications are significantly different from traditional web workloads, and whether they present new challenges to underlying systems. In this paper, we present a detailed characterization of three Web 2.0 workloads, and a synthetic benchmark representing commercial workloads that do not exploit Web 2.0, for comparison.

show abstract

A performance methodology for commercial servers

Cited by 42 publications

References 23 publications

Exploring power management in multi-core systems

Exploring power management in multi-core systems

Interconnections in Multi-Core Architectures: Understanding Mechanisms, Overheads and Scaling

Workload characterization of selected JEE-based Web 2.0 applications

Contact Info

Product

Resources

About