By Jung W. Suh, Youngmin Kim
Past simulation and set of rules improvement, many builders more and more use MATLAB even for product deployment in computationally heavy fields. This usually calls for that MATLAB codes run speedier via leveraging the dispensed parallelism of pix Processing devices (GPUs). whereas MATLAB effectively offers high-level features as a simulation software for swift prototyping, the underlying info and information wanted for using GPUs make MATLAB clients hesitate to step into it. Accelerating MATLAB with GPUs deals a primer on bridging this gap.
Starting with the fundamentals, establishing MATLAB for CUDA (in home windows, Linux and Mac OS X) and profiling, it then courses clients via complex issues comparable to CUDA libraries. The authors percentage their event constructing algorithms utilizing MATLAB, C++ and GPUs for enormous datasets, editing MATLAB codes to raised make the most of the computational energy of GPUs, and integrating them into advertisement software program items. in the course of the e-book, they show many instance codes that may be used as templates of C-MEX and CUDA codes for readers' tasks. obtain instance codes from the publisher's web site: http://booksite.elsevier.com/9780124080805/
• indicates how you can speed up MATLAB codes in the course of the GPU for parallel processing, with minimum knowledge
• Explains the comparable historical past on undefined, structure and programming for ease of use
• offers basic labored examples of MATLAB and CUDA C codes in addition to templates that may be reused in real-world initiatives
Read or Download Accelerating MATLAB with GPU Computing: A Primer with Examples PDF
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Extra info for Accelerating MATLAB with GPU Computing: A Primer with Examples
The pump is freed by the statement following the subroutine oall CALL ADVANC by the statement IPUMP = O. Sinoe IPUMP occurs in the condition NCOND = I, this must be tested immediately. This is initiated by setting the test flag TTEST = T. IPUMP TTEST 0 T The test indicator causes the subroutine TEST to be called. This tests the oondition NCOND = 1 and, if necessary, causes a transaction to be unblocked. , it is not necessary to unblock all transactions at the gate. Note: * In this very simple example it would be possible to test the oondition in the subroutine ACTIV rather by calling the subroutine TEST: IPUMP = 0 IF(CHECK(l))CALL DBLOCK(5,l,O,l) It is also possible to omit the test of the condition oompletely, since the condition is certainly satisfied when the test is performed.
8 Problems These examples demonstrate further applioations Version 3. of GPSS-FORTRAN * Problem 1 If the number of hosts beoomes less than the value XMIN or the number of parasites beoomes greater than YMAX, then the number of parasites is to be halved. This reduotion of the number of parasites is to take plaoe 20 time units later. The number of parasites is not to be reduoed again during this period, for example when the number of parasites exoeeds the upper bound YMAX and shortly afterwards the number of hosts beoomes less than the value XMIN.
In addition the transaction array, the arrays used by the flow control, and the contents of the queue at the gate are to be printed out. Note: System variables are printed using the report subroutines of GPSS-FORTRAN Version 3. REPRT1(NT) Print the queues at the stations with type index NT. For gates NT = B. REPRT2 Print the transaction array and the family array. (The family array is meaningless in this example). REPRT3 Print the flow control arrays. have no parameters. 2 Running of the Model 47 Thus the event is as following: C 1 IPRINT ~ 0 CALL REPRTl(5) CALL REPRT2 CALL REPRT3 RETURN Note: * If several activities are scheduled to take place at the same time, then events are activated before other activities.