From 686994735b2ae601810875a1032a599f3f219777 Mon Sep 17 00:00:00 2001 From: Ling K Date: Fri, 10 May 2019 00:36:50 +0100 Subject: [PATCH] Create README.md --- README.md | 55 +++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 55 insertions(+) create mode 100644 README.md diff --git a/README.md b/README.md new file mode 100644 index 0000000..d16d2d8 --- /dev/null +++ b/README.md @@ -0,0 +1,55 @@ +![University of Lincoln](http://thelincolnite.co.uk/wp-content/uploads/2012/07/new_uni_crest.jpg "University of Lincoln") +---------- + +# CMP3110M Parallel Computing, Assessment Item 1 +Your task is to develop a simple statistical tool for analysing historical weather records from +Lincolnshire. The provided data files include records of air temperature collected over a period of +more than 80 years from five weather stations in Lincolnshire: Barkston Heath, Scampton, +Waddington, Cranwell and Coningsby. Your tool should be able to load the provided dataset and +perform statistical summaries of temperature including the min, max and average values, and standard +deviation. The provided summaries should be performed on the entire dataset regardless their +acquisition time and location. For additional credit, you can also consider the median statistic and its +1st and 3rd quartiles (i.e. 25th and 75th percentiles) which will require a development of a suitable +sorting algorithm. + +Due to the large amount of data (i.e. 1.8 million records), all statistical calculations shall be performed +on parallel hardware and implemented by a parallel software component written in OpenCL. Your tool +should also report memory transfer, kernel execution and total program execution times for +performance assessment. Further credit will be given for additional optimisation strategies which +target the parallel performance of the tool. In such a case, your program should run and display +execution times for different variants of your algorithm. Your basic implementation can assume +temperature values expressed as integers and skip all parts after a decimal point. For additional credit, +you should also consider the exact temperature values and their corresponding statistics. + +You can base your code on the material provided during workshop sessions, but you are not allowed to +use any existing parallel libraries (e.g. Boost.Compute). To help you with code development, a shorter +dataset is also provided which is 100 times smaller. The original file is called +“weather_lincolnshire.txt” and the short dataset is “weather_lincolnshire_short.txt”. More details +about the file format are included in the “readme.txt” file. The data files are provided on Blackboard +together with this description document in a file “temp_lincolnshire_datasets.zip”. The output results +and performance measures should be reported in a console window in a clear and readable format. All +reading and displaying operations should be provided by the host code. + +The main assessment criteria for this task are related to the correctness of the developed algorithms +and effectiveness of optimisation strategies. The code should be well commented and clearly structured into functional blocks. + +---------- + + +## Objectives + + +* [LO1] demonstrate practical skills in applying parallel algorithms for solving computational +problems; +* [LO3] analyse parallel architectures as a means to provide solutions to complex computational +problems. + +---------- + + +## License + +The program is licenced under [GPL Version 2.0](https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html). The source is freely available to use, compile and modify. + + +----------