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Below are some mashups showing the frequency density of where I have ridden my bikes in the last three years. (I never use my GPS on the track, so velodrome riding is not represented here. And besides, that isn’t very interesting.) The circles on the maps represent a place I have passed through, and the color how many times. Red means many, perhaps as many as 5000 times for the area near my apartment, and blue means few, as few as once. That 5000 doesn’t mean I’ve done 5000 rides, it means that there are 5000 GPS waypoints in the 100 meter radius circle around that particular point. As waypoints are recorded closer than 100m apart, the same ride could have multiple waypoints inside each circle. Also note that the circles on the map are much larger than 100m.
Click on each for a larger view.
Update: 19 April 2009 I made a Google Earth KMZ file containing all the points. If you open it, be patient as it will take a bit of time to load. Download it here.
I think I’m planning on posting the code here and at the forums on Motionbased, as I think other people might like this fun bit of code. But I want to clean it up a bit before I make it public.
The graph above shows the speedup that a few OpenMP statements can give with very little effort. OpenMP is a simple way to parallelize a C/C++ program which allows you to run a program on many processors at once. However, unlike MPI which can run on many different machines (like a cluster), OpenMP can only be run on one computer at a time. Since most new machines have multiple processors (or cores), OpenMP is quite useful.
I’ve added a couple dozen OpenMP statements to the code I’m working on. The blue line shows how long (in seconds) it took me to run a test problem on between one and 32 processors. The green line shows the speedup compared to running on a single processor as a ratio of time. It is very typical of parallel programs that the speedup isn’t linear and flattens out at high thread count. This small test problem deviates at 16 processors; when I do a real run (which will be much larger and the parallelization more efficient) I may see nearly linear speedups all the way to 32 processors.
I think it’s pretty neat how with very little effort I was able to significantly speedup my code. If you have a little programming experience, you can take a look at some simple OpenMP examples and see for yourself just how easy OpenMP is.
I’ve had my Motorola E815 phone for about a year. It has bluetooth, a camera, and other cool features, like many modern phones. Bluetooth enables you to transfer photos, movies and ringtones on and off a phone. All these things seem like a useful feature set for a phone. However, Verizon, the carrier for my current phone, disabled a number of bluetooth features, such as file transfer.
Why would Verizon intentionally cripple a phone? Money, of course. Turning off the file transfer abilities of a phone means that if I want to get the photos I take using my phone onto my personal computer, I need to use their not free services. Also, if I want to get a new ringtone, I need to pay for them (often over a buck for 30 seconds of music!), instead of uploading a simple, free, MIDI I found on the internet.
Ever since I got my phone, I’ve been aware that it is easily hacked to allow all bluetooth function, but it required a special USB cable. I never got around to buying the $10 cable, and hacking the phone, until now.
The camera actually takes farily decent photos in a wide range of light conditions considering it’s just a pinhole lens. It also takes short movies, with sound. I can also upload MIDI sound files, or even MP3s, and make them my ringtone. I’ve always wanted to pull out my camera phone whenever I saw something cool, but never bothered because I couldn’t get them off the camera for free. Now that I can, I’ll be more willing to snap a pic of whatever.
Just a few days ago, I replaced my four year old white 500 Mhz G3 iBook with a shiny widescreen white 1.83 Ghz Intel Core Duo MacBook (the black one seemed altogether silly to spend extra money on). The laptop is a very nice machine. My home machine is a 20″ iMac G5 with a widescreen, and I’ve gotten used to the extra real estate, so I like the fact that the MacBook has one too. Really, the main reason I bought it is because my iBook had decayed to the point that it was only good for websurfing. I wanted a machine I could use at school, and the iBook just couldn’t cut it (I definitely tried to make the iBook work!).
Since Apple is switching to Intel chips, the world of Windows is now available using either Boot Camp or Parallels. I have a copy of Windows 2000, and since I believe that Boot Camp only works with Windows XP, I am not going to try that out. Also, Boot Camp makes your machine dual-boot, which means only one OS at a time and no interaction between the two. Parallels is the more attractive option, it allows you to run Windows along with Mac OS X. The Windows world lives inside of an application that runs on Mac OS X. Choosing to interact with Windows is no more difficult that switching applications. Also, Parallels works with basically any Intel-compatible operating system, so I could use my Win2000 install disk.
After much trial and tribulation (mainly related to the fact that my Win2000 is an upgrade version, not full install) I got Win2000 installed using Parallels on my MacBook. After installing the myriad of security updates, I installed the softwares for my Garmin Forerunner 301. You see, Garmin (right now) only makes software for their gadgets for Windows. They’ve promised to make a Mac OS X verison of the software I use by Spring 2006 (they have two and a half weeks). Obviously, waiting around for that to be relased will just waste my time, so I was hoping that I could use this whole setup to run the Windows software on my MacBook to talk to my GPS. However, sadly, it doesn’t work. It’s clear it almost works, since Win2000 notices when I plug in the GPS, but the Garmin stuff can’t quite talk to the GPS. The situation seems exactly the same as when I tried using Virtual PC on my G5 over a year ago.
All in all, I like the laptop, I like Parallels, and I’m displeased with Garmin. I’m using a beta 30-day activation key with Parallels, and I’m unsure if I’ll buy the full version ($40 for pre-ordering). I really try to stay away from Windows applications. Right now the only app I do want to run is the Garmin stuff, and it doesn’t look like that’s going to work.
I recently stumbled across GPS Visualizer.com. It’s an amazing website full of all kinds of GPS tools. The one I found to be useful was the Google map tool. It can take all kinds of GPS data files, and it outputs the route superimposed on a draggable Google map. Since I use a Garmin Forerunner 301, I can use the GPS data to make a Google map route.
There are two ways I can go about this:
Upload my data to Motionbased.com, which then allows me to download the route as either a KML or GPX file. I then give that to GPS Visualizer.
Use LoadMyTracks to download the data off my GPS to my iMac, and then (after some parsing) upload that file to GPS Visualizer.
So far I’ve only done a few of the routes, but herearesomeexamples. So for all you fans of me out there in cyberspace, keep checking back for new Google map cycling routes!