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Optimization of System Performance using OpenMP. m5151117 Yumiko Kimezawa. Outline. Problems with Previous Research What is OpenMP and MPI ? A brief example of OpenMP Research Goal Future Work. Problems with Previous Research. The scale of systems is large Accuracy of PPD Algorithm
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RPS Optimization of System Performance using OpenMP m5151117 Yumiko Kimezawa
Outline RPS • Problems with Previous Research • What is OpenMP and MPI ? • A brief example of OpenMP • Research Goal • Future Work
Problems with Previous Research RPS • The scale of systems is large • Accuracy of PPD Algorithm • A/D converters are not implemented • Raw ECG data is analog data PPD Algorithm will be optimized by using OpenMP or MPI
What are OpenMP and MPI ? RPS • OpenMP • A shared-memory application programming interface (API) • Facilitator of shared-memory parallel programming • Is used on a board range of SMP architecture • Is usually used to parallelize loops • MPI • Message Passing Interface • Programming for distributed-memory architecture • Multiple processes operate independently
A brief example of OpenMP RPS Fork-join programming model Initial threads Fork Team of threads Join Initial threads Thread 0: for(i=0; I < 25; i++) sum += i; Thread 1: for(i=25; I < 50; i++) sum += i; Thread 2: for(i=50; I < 75; i++) sum += i; Thread 3: for(i=75; I < 100;I ++) sum += i; Sum +
Research Goal RPS • Optimization of • the HW • Implementation of the A/D converter • the SW • Parallelization of algorithm • Improvement of accuracy of algorithm • Real-time evaluation • - Conclusive results are sent to the web
Future Work RPS • Continue to study OpenMP • Research of other algorithms
Period-Peaks Detection (PPD) Algorithm (2/2) RPS Peaks processing Data reading Extraction Derivation Discrimination Autocorrelation Store of results Finding interval Period detection
Period-Peaks Detection (PPD) Algorithm (2/2) RPS Equation Peaks processing Data reading Extraction Derivation Discrimination Autocorrelation : Current sampling data (filtered ECG signals) Store of results Finding interval : Current time (step) Period detection
Period-Peaks Detection (PPD) Algorithm (2/2) RPS Autocorrelation function Peaks processing Data reading Extraction Derivation Discrimination Autocorrelation : The autocorrelation function : The filtered ECG signal Store of results Finding interval : The number of times needed for the calculations to get the period(256 in our program) Period detection
Period-Peaks Detection (PPD) Algorithm (2/2) RPS Peaks processing Data reading Extraction Derivation Discrimination Autocorrelation Store of results Finding interval Period detection
System architecture RPS : Data flow : Control signal LED Graphic LCD JTAG UART External Memory ECG Data Rom Slave CPU LED Controller Graphic LCD Controller Slave CPU Memory Avalon Bus Master CPU Timer Master CPU Memory FIR Filter Shared Memory Timer Master Module PPD Module
System architecture RPS 1: Signal Reading : Data flow : Control signal LED Graphic LCD JTAG UART External Memory ECG Data Rom Slave CPU LED Controller Graphic LCD Controller Slave CPU Memory Avalon Bus Master CPU Timer Master CPU Memory FIR Filter Shared Memory Timer Master Module PPD Module
System architecture RPS 2: Filtering : Data flow : Control signal LED Graphic LCD JTAG UART External Memory ECG Data Rom Slave CPU LED Controller Graphic LCD Controller Slave CPU Memory Avalon Bus Master CPU Timer Master CPU Memory FIR Filter Shared Memory Timer Master Module PPD Module
System architecture RPS 3: Analysis : Data flow : Control signal LED Graphic LCD JTAG UART External Memory ECG Data Rom Slave CPU LED Controller Graphic LCD Controller Slave CPU Memory Avalon Bus Master CPU Timer Master CPU Memory FIR Filter Shared Memory Timer Master Module PPD Module
System architecture RPS 4: Display : Data flow : Control signal LED Graphic LCD JTAG UART External Memory ECG Data Rom Slave CPU LED Controller Graphic LCD Controller Slave CPU Memory Avalon Bus Master CPU Timer Master CPU Memory FIR Filter Shared Memory Timer Master Module PPD Module