scholarly journals SERVOGrid complexity computational environments (CCE) integrated performance analysis

2005 ◽  
Author(s):  
G. Aydin ◽  
M.S. Aktas ◽  
G.C. Fox ◽  
H. Gadgil ◽  
M. Pierce ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Integrated Performance

Coexistence of IEEE 802.11b and Bluetooth: An Integrated Performance Analysis

2007 ◽  
Vol 12 (5-6) ◽  
pp. 450-459 ◽  
Author(s):  
Min Song ◽  
Sachin Shetty ◽  
Deepthi Gopalpet
Keyword(s):  
Performance Analysis ◽  
Ieee 802.11B ◽  
Integrated Performance

Scalable integrated performance analysis of multi-gigabit networks

2012 ◽  
Author(s):  
E. Kissel ◽  
A. El-Hassany ◽  
G. Fernandes ◽  
M. Swany ◽  
D. Gunter ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Integrated Performance ◽  
Gigabit Networks

Integrated Performance Analysis of Latent Heat Storage and Finned Type Solar Distiller

2012 ◽  
Vol 4 (5) ◽  
pp. 613-616 ◽  
Author(s):  
M. Gowtham ◽  
K. Richard Neiel ◽  
V. Nagarajan ◽  
P. Christhu Dass ◽  
A. Thimothy
Keyword(s):  
Performance Analysis ◽  
Latent Heat ◽  
Heat Storage ◽  
Latent Heat Storage ◽  
Integrated Performance

scholarly journals Perancangan Sistem Pengukuran Kinerja Terintegrasi Pada Program Studi Teknik Mesin Universitas Udayana

2018 ◽  
Vol 11 (1) ◽  
pp. 15
Author(s):  
I Made Dwi Budiana Penindra ◽  
Dewa Made Priyantha Wedagama
Keyword(s):  
Performance Analysis ◽  
Performance Measurement ◽  
Measurement System ◽  
Performance Indicator ◽  
Performance Measurement System ◽  
Traffic Light ◽  
Measurement Systems ◽  
Period 2 ◽  
Performance Measurement Systems ◽  
Integrated Performance

Jurusan Teknik Mesin merupakan salah satu jurusan yang terakreditasi A. Jurusan Teknik Mesin Universitas Udayana pada tahun 2016 telah berhasil mempertahankan akreditasi A yang diperoleh sejak tahun 2011. Salah satu penunjang keberhasilan tersebut adalah karena telah dimilikinya sistem pengukuran kinerja yang dihasilkan penulis pada tahun 2015 dimana sistem tersebut telah mampu memantau kinerja jurusan secara berkesinambungan. Walaupun sistem pengukuran kinerja tersebut telah digunakan, tetapi pada implementasinya masih banyak kekurangan yang dimiliki oleh sistem tersebut terutama karena sistem tersebut masih berbentuk manual.  Kekurangan lain juga  dapat dilihat dari hasil penelitian penulis tahun 2016 yang menunjukkan bahwa dari Importance Performance Analysis (IPA) rata-rata persepsi dari mahasiswa sebesar 2,91 masih dibawah rata-rata ekspektasi mereka yaitu 3,14. Pada penelitian ini dilakukan perancangan kembali  sistem pengukuran kinerja yang terintegrasi berdasarkan hasil-hasil penelitian di tahun 2015 dan 2016 dengan metode Performance Prism dimana metode tersebut diintegrasikan dengan beberapa metode yaitu Integrated Performance Measurement Systems (IPMS) di dalam penentuan Key Performande Indicator (KPI) yang menjadi indikator penentu kinerja yang kemudian dibantu menggunakan metode Analytical Hierarcy Process (AHP) di dalam pemberian bobot masing-masing KPI. Setelah KPI memiliki bobot kemudian dilakukan scoring secara menyeluruh dengan Metode Objectives Matrix (OMAX) sehingga dihasilkan angka indeks per periode yang menjadi acuan tingkat kinerja jurusan, serta Traffic Light System (TLS) untuk mengetahui KPI mana yang memerlukan perbaikan berdasarkan warna. Dari hasil penelitian didapatkan hasil Performance Indicator dari periode 1 sebesar 322,8 dan mengalami peningkatan 7,6% dibanding Performance Indicator rata-rata 300. Performance Indicator dari periode 2 sebesar 352,50 dan mengalami peningkatan 9,2% dibanding periode 1. Performance Indicator dari periode 3 sebesar 354,66 dan mengalami sedikit peningkatan 0,61% dibanding periode 2. Performance Indicator dari periode 4 sebesar 354,52 dan mengalami sedikit penurunan 0,04% dibanding periode 3. Performance Indicator dari periode 5 sebesar 573,35 dan mengalami peningkatan 61,73% dibanding periode 4. Performance Indicator dari periode 6 sebesar 606,68 dan mengalami peningkatan 5,81% dibanding periode 5 dan merupakan periode dengan Performance Indicator tertinggi dalam sistem pengukuran ini. Department of Mechanical Engineering Udayana University in 2016 has managed to maintain the A accreditation obtained since 2011. One of the supporting success is because it has owned performance measurement system generated by the author in 2015 where the system has been able to monitor the performance of majors on an ongoing basis. Although the performance measurement system has been used, but in its implementation there are still many shortcomings possessed by the system mainly because the system is still in the form of manual. Another disadvantage can also be seen from the results of research authors of 2016 which shows that from the Importance Performance Analysis (IPA) average perception of students of 2.91 is still below the average of their expectations of 3.14. In this research, re-design of integrated performance measurement system based on the results of research in 2015 and 2016 with Performance Prism method where the method is integrated with several methods of Integrated Performance Measurement Systems (IPMS) in the determination of Key Performande Indicator (KPI) a performance indicator that is then assisted using the Analytical Hierarcy Process (AHP) method in the weighting of each KPI. After KPI has weight then scoring thoroughly with Objectives Matrix (OMAX) method so that the result of index number per period become reference of department performance level, and Traffic Light System (TLS) to know which KPI need improvement based on color. From the research results obtained Performance Indicator from period 1 of 322.8 and increased 7.6% compared to Performance Indicator average 300. Performance Indicator from period 2 amounted to 352.50 and increased 9.2% compared to period 1. Performance Indicator from period 3 was 354.66 and slightly increased by 0.61% compared to period 2. Performance Indicator from period 4 was 354.52 and decreased slightly 0.04% compared to period 3. Performance Indicator from period 5 was 573.35 and an increase of 61.73% compared to period 4. Performance Indicator from period 6 of 606.68 and increased 5.81% compared to period 5 and is the period with the highest Performance Indicator in this measurement system.

scholarly journals Open | SpeedShop: An Open Source Infrastructure for Parallel Performance Analysis

2008 ◽  
Vol 16 (2-3) ◽  
pp. 105-121 ◽  
Author(s):  
Martin Schulz ◽  
Jim Galarowicz ◽  
Don Maghrak ◽  
William Hachfeld ◽  
David Montoya ◽  
...  
Keyword(s):  
Performance Analysis ◽  
High Performance ◽  
Large Scale ◽  
Parallel Applications ◽  
Set Covering ◽  
Command Line ◽  
Command Line Interface ◽  
Parallel Performance ◽  
Tool Set ◽  
Integrated Performance

Over the last decades a large number of performance tools has been developed to analyze and optimize high performance applications. Their acceptance by end users, however, has been slow: each tool alone is often limited in scope and comes with widely varying interfaces and workflow constraints, requiring different changes in the often complex build and execution infrastructure of the target application. We started the Open | SpeedShop project about 3 years ago to overcome these limitations and provide efficient, easy to apply, and integrated performance analysis for parallel systems. Open | SpeedShop has two different faces: it provides an interoperable tool set covering the most common analysis steps as well as a comprehensive plugin infrastructure for building new tools. In both cases, the tools can be deployed to large scale parallel applications using DPCL/Dyninst for distributed binary instrumentation. Further, all tools developed within or on top of Open | SpeedShop are accessible through multiple fully equivalent interfaces including an easy-to-use GUI as well as an interactive command line interface reducing the usage threshold for those tools.

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