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It’s been rather quiet around here for the past couple of weeks. This is why:
After I get back from a much needed break, I’ll get an alpha release ready. In the meantime, use the source, Luke.
Update: If you haven’t figured it out by now, we’re holding off on future development until Apple releases the SDK in February 2008.
Sometimes it takes awhile to fulfill a promise.
One such pledge was made last century to my good friend Jeffrey (he was only a prince at the time.) I said that I’d love to write something for his fledgling mailing list: A List Apart. This past month, I finally got around to writing that piece: Put Your Content in My Pocket.
If you’re visiting this site for the first time, you might be interested in the original article that prompted our collaboration. I’ve also written some articles that explore some of the problems, performance and less than obvious features on the iPhone. For the hard core geeks, there are also some explorations into the specifications.
So enjoy your visit and please make sure to join in the discussion forum at ALA if you have any questions or concerns about my article. Thanks!
Postscript: I mentioned some nonsense in the article: here it is, the Eric Meyer Memorial iPhone Blocker.
The iPhone technical specifications mention nothing about how much RAM is included nor how fast the CPU is running. Now that I have a toolchain, it was a simple task to take some code from iPulse to investigate.
Note: Apple has obviously not documented the system level APIs that I’m using to extract this information, so take these numbers with a grain of salt. Personally, I doubt that they would bother to make these low-level functions report erroneous information just to protect some consumer spec sheet, so it’s likely that they’re close if not exact.
First, let’s start off with memory. Calling host_statistics() with HOST_VM_INFO returns a count of the number of memory pages in use (the “vm_stat” tool at the command line does the same thing.) Totaling these counts shows that there are 19,500 pages of memory with each page being 4096 bytes. That’s 78,000 KB or 76.2 MB.
Another way to determine memory size is by calling sysctl() with CTL_HW and HW_PHYSMEM. This results in 121,634,816 bytes or 117 MB being reported for physical memory. Similarly, user memory is reported as 93,605,888 bytes or 89.3 MB—close to the 76.2 MB reported by host_statistics(). These calls are equivalent to using “sysctl hw.physmem” and “sysctl hw.usermem” from the Mac OS X command line.
None of these numbers are the nice round powers of 2 that we’re so accustomed to. I suspect that there is some kind of memory partitioning: something like a graphics chip could be using 11 MB of memory and that combined with the 117 MB of physical memory would bring the RAM total to 128 MB.
Now let’s take a look at the CPU speed. Again, sysctl() is our friend, this time using CTL_HW with HW_CPU_FREQ and HW_BUS_FREQ. The results of our test show that the CPU is specified at 400 Mhz with a bus frequency of 100 Mhz.
There have been various hardware reports that place the ARM chip’s frequency above 600 Mhz. Maybe sysctl() is lying to us, or maybe the CPU is clocked down to give improved battery life. Only Apple knows that for sure.
For those of you who care, the source code used for the tests is available.
There are two things that I really want on my iPhone: Twitterrific and Frenzic. Last week I started taking care of the first one and am happy to announce a proof-of-concept.
Don’t expect much in terms of usability or elegance. The application only initiates a network connection to Twitter, downloads a timeline feed as XML, and then parses it into a data model. The user name from the model is then displayed in a table view. Sounds pretty simple, right?
Bzzzzt.
It took a lot of head scratching to parse that XML data. NSXMLDocument is hidden in the OfficeImport framework (presumably to handle Office XML files.) The ARM linker can’t see the symbol in the framework, so the document is instantiated with [NSClassFromString(@”NSXMLDocument”) alloc]. Many thanks go to Lucas Newman for figuring that one out! Also, there aren’t any XPath methods available, so extracting the information isn’t as easy as with AppKit.
(Do a search for “NOTE:” in the source code for more information on the cause and resolution to these problems.)
It’s pretty clear that the development of a native Twitter client should be done “in the open.” There’s a lot of reverse engineering involved while developing native iPhone applications, so getting more brains involved will result in much quicker development. It will also aid in the development of similar types of network-based applications, such as Ian Baird’s Pownce client. It’s also my hope that this project will spur Brent Simmons into doing something creative :-)
So take a look at MobileTwitterrific, and if you think you can help out, please get in touch via my Gmail account. Thanks!
