GLM Science Meeting September 29-30, 2009 1 Update on GLM Cluster/Filter Algorithm Testing Douglas Mach, UAHuntsville Monte Bateman, USRA GLM AWG/R3 Science.

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Presentation transcript:

GLM Science Meeting September 29-30, Update on GLM Cluster/Filter Algorithm Testing Douglas Mach, UAHuntsville Monte Bateman, USRA GLM AWG/R3 Science Meeting 2009

GLM Science Meeting September 29-30, Outline 1.Status of GLM CFA a.Version 3 Details b.Horseshoes_Hangrenades Routine 2.CFA Improvements a.Memory Management b.Error Detection 3.Proxy Data a.Type Definitions b.Details on GLM Proxy Data c.New Proxy Data Requests 4.Future Tasks 5.Questions

GLM Science Meeting September 29-30, Status of GLM CFA Version 3 code submitted to NOAA AIT on 6/30/09 Version 4 due to NOAA AIT 2/25/10 Version 3 currently being assimilated into NOAA AIT Framework Current version is able to process ~20k events/s Uses single processing thread (no regionalization or parallelization) (details next set of slides)

GLM Science Meeting September 29-30, a. Version 3 CFA Details Version 3 code submitted to NOAA AIT on 6/30/09 –Better memory management –Error detection –Numerous code tweaks to speed processing

GLM Science Meeting September 29-30, a. Version 3 CFA Details (cont.) Version 3 currently being assimilated into NOAA AIT Framework –Global variables to be handled by Framework, not CFA –Most memory allocation to be handled outside of CFA code (by Framework) –I/O to be handled by Framework (NetCDF format) –In contact with AIT folks for any integration issues

GLM Science Meeting September 29-30, a. Version 3 CFA Details (cont.) Current version is able to process 20k events/s –Reasonable datasets with data rates up to 25k events/s can be processed by the CFA within 1 s of computer time –Somewhat non-linear function of event rate –“Pending flashes/groups/events count” is key parameter

GLM Science Meeting September 29-30, a. Version 3 CFA Details (cont.) Uses single processing thread (no regionalization or parallelization) –Overhead to keep track of regionalization much greater than originally thought Boundaries of regions Join/split regions Tracking regions –Found alternative method to “cheat” effects of regionalization without the overhead code –Horseshoes_Handgrenades (H_H) routine (details next)

GLM Science Meeting September 29-30, b. Secret of H_H Routine Most time spent finding which active flash a new event is associated with (“search space”) As data rates increase, search space increases H_H routine “cheats” by first checking one location per flash to see if the new event is “close” to the flash –If so, it checks all groups in the flash –If not, the code skips to the next flash (Example next slide)

GLM Science Meeting September 29-30, b. Secret of H_H Routine (cont.)

GLM Science Meeting September 29-30, b. Secret of H_H Routine (cont.) Definition of “close” needs to be tuned –Too large & time savings decrease –Too small & large flashes could be split –Currently defined as 3° Lat/Lon Able to speed clustering without regionalization code overhead

GLM Science Meeting September 29-30, CFA Improvements Memory Management –Code allocates “typical” memory buffers for events, groups, flashes, children pointers, parent pointers, etc. –As needs increase, the code is able to allocate more memory for buffers (but never de-allocates) –Code handles inability to allocate more memory (computer error) by truncating flashes (no data loss) rather than crashing, which is what it did before –Need to tune the definition of “typical” for memory management Use too much memory vs. Spending too much time allocating new buffers (with possibility of memory leaks)

GLM Science Meeting September 29-30, CFA Improvements (cont.) Error Detection –Detects errors in amplitude & location Events thrown out if values out of range No attempt (in V3) to correct amplitude/location errors

GLM Science Meeting September 29-30, CFA Improvements (cont.) Time errors are handled differently –Time errors do not result in events being thrown out –Forward time jumps are “ignored” if large enough, more or less “flush” pending flash list –Backward time jumps “flushes” the pending flash list

GLM Science Meeting September 29-30, Types of Proxy Data –Speed Tests A speed test checks how many events per second the LCFA can process, and determines if the LCFA can keep up with latency requirements. –Accuracy Tests An accuracy test involves first constructing (by simulation or by using a data source) an event-level dataset. Next, one clusters the event-level dataset to construct a known flash-level dataset. Finally, the event-level dataset is input to the LCFA and the LCFA output is compared to the known flash-level dataset to assess LCFA clustering accuracy. Note that the input event-level dataset has no errors (effect of input errors is examined in resiliency tests). –Resiliency Tests A resiliency test examines how well the LCFA can control/minimize the deleterious effects of input errors or other peculiar/unusual input conditions (e.g., event radiance noise or location errors, corrupted data packets, extremely long-duration flashes, events near the prime-meridian or international date-line, negative event times, event times that run backwards, latitudes/longitudes that are out-of-range, etc.). 3. Proxy Data

GLM Science Meeting September 29-30, Proxy Data (cont.) Details on GLM Proxy Data –The best proxy we have for GLM is the LIS (optical) –LIS is a LEO sensor, so it presents a transient view of storms –The LMA (VHF) is a 24x7 total lightning sensor –VHF and optical instruments are sensitive to different parts of the lightning flash –Need a mapping from LMA (24x7) to LIS (optical) –That mapping has been developed using a coincidence study incorporating many years of LMA+LIS data –Using this mapping, proxy data based on real LMA data have been generated and processed through the Mach’s cluster algorithm. –Results are being evaluated…

GLM Science Meeting September 29-30, Need new proxy data types to test code –Large mesoscale systems with frequent, realistic lightning test code’s ability to separate individual lightning flashes –“Realistic” large (full GLM FOV) datasets with “bursty” lightning to test code’s ability to handle and then recover from high data rate periods –“Realistic” datasets tied to some ABI test datasets so that lightning can be associated with ABI features may need to be in other regions of the world 3. Proxy Data (cont.)

GLM Science Meeting September 29-30, Future Tasks Assist with integration of V3 code into AIT Framework system Develop V4 code –Within Framework –Under software configuration management (Rational® ClearCase®) –NetCDF I/O –Better error handling (some error correction) –Optimize code for further speed improvements Assist in developing new proxy datasets Look at parallelization –Code has 3 “threads” Input read/filter Cluster/filter Output write/filter –May not be needed

GLM Science Meeting September 29-30, Questions?