Efficiency of small size tasks calculation in grid clusters using

parallel processing

Efficiency of small size tasks calculation in grid clusters using

parallel processing..

Olgerts BelmanisJānis Kūliņš

RTU ETF

Riga Technical University

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Krakow, CGW 07 , 15-16 Okt 2

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RTU ClusterRTU Cluster

■ Initially RTU cluster started with five servers

AMD Opteron 146. 1TB■ Additionaly was installed eight dual core AMD

Opteron 2210 M2. ■ Therefore now there are 9 working nodes

with 21 CPU units. ■ Total amount of memory is 1,8 TB. ■ RTU cluster successfully completed many

calculation tasks including LHCB virtual organization orders.

Krakow, CGW 07 , 15-16 Okt

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RTU ClusterRTU Cluster

Krakow, CGW 07 , 15-16 Okt

RTU ClusterRTU Cluster

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Computing AlgorithmsComputing Algorithms

■ Serial algorithm

One task – one WN (working node);

Parts of task performed serial;

Task execution time depend on WN performance only!

■ Paralel algorithm

One task – several WN; Parts of task performed:

► Consecutive on separate WN

► In parallel on number of WN; rezults summerizing

Task execution time depend on:

► WN performance;► Network performance;► Bandwith of shared data

stocks;► Type of coding

.

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Bottlenecks in distributive computing system

Bottlenecks in distributive computing system

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Interconnections between CPU nodesInterconnections between CPU nodes

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************************************************************task 0 is on wn03.grid.etf.rtu.lv partner= 2task 1 is on wn10.grid.etf.rtu.lv partner= 3task 1 is on wn10.grid.etf.rtu.lv partner= 3task 2 is on wn10.grid.etf.rtu.lv partner= 0task 2 is on wn10.grid.etf.rtu.lv partner= 0task 3 is on wn10.grid.etf.rtu.lv partner= 1task 3 is on wn10.grid.etf.rtu.lv partner= 1

***************************************************************Message size: 1000000 *** best / avg / worst (MB/sec)

task pair: 0 - 2: 103.31 / 102.29 / 53.64 task pair: 1 - 3: 371.33 / 197.63 / 134.05 task pair: 1 - 3: 371.33 / 197.63 / 134.05 OVERALL AVERAGES: 237.32 / 149.96 / 93.84

...use of multicore servers help to achieve higher data transmission rate in MPI applications!

Krakow, CGW 07 , 15-16 Okt

Local interconnection rateLocal interconnection rate

CPU numberLow rate

Mb/s Medium rate Mb/sPeek rate

Mb/s

4 95 140 240

6 18 60 90

8 3 60 98

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Transmission rate dependence of number of CPU....MPI used number of CPU have influence to

intermediate connection rate!!!

Krakow, CGW 07 , 15-16 Okt

Parallel application execution timeParallel application execution time

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Paralel speedup determinationParalel speedup determination

■ During experiment multiplication of large matrixes has been done.

■ Test create traffic between WN more than some 10 Mb and loaded processors.

■ Main task of the experiment is to find beginning of horizontal part of speed up curve.

■ Experiment on 1 CPU in RTU cluster takes 420 seconds.

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2x WN ≠ H/22x WN ≠ H/2

...according to Amdal’s law that speed-up conform with 20% serial algorithm code!

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Possible solutions:Possible solutions:■ Internal connection improvement:

Infiniband, Myranet….connections between WN; Multicore WN implementation (RTUETF); NFS network file system abandonment.

■ Data transfer process optimizing: Number of flows using; Replace standard TCP protocol to Scalable TCP;

■ Parallel algorithm processing optimization: Minimize transactions between WN; Reduce sequential part of MPI code; Optimization of MPI threat number.

■ Optimization of requested resource management

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Krakow, CGW 07 , 15-16 Okt

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Thank you for attention!

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