"I have a mind like a steel... uh... thingy." Patrick Logan's weblog.

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Thursday, September 22, 2005

Threads, Processes (and Shared Memory)

James Robertson quotes from several interesting pieces on threads, processes, and programming models. I am squarely in the multi-process camp too. I remember my absolute shock about a decade ago when I learned Java (at that time aimed at being a simple web programming language) had a shared-memory with monitors concurrency model.

The key phrase there is "shared-memory". Threads in and of themselves are not the problem. The shared-memory model is the real problem.

With a shared-nothing model then threads take on much more of a "process" feel. Languages like Erlang and Termite implement lightweight shared-nothing processes above the level of the OS. The benefits of sharing lightweight processes within a single address space provide a "best of both worlds" model. Sharing can take place under the abstraction of the language... the runtime benefits of sharing but the developer-time benefits of isolation. Whether an associated process is local, or in another OS process, or on another node, is irrelevant in many respects. Performance, reliability, etc. are still concerns so the distribution problem is not completely abstracted away.

Wednesday, September 21, 2005

Smalltalk Leading the Way

David Buck writes about an enticing upcoming meeting of the Ottawa Smalltalk User Group...

Smalltalk and Smalltalk developers have led the way to the modern techniques and practices that [David] teaches in Simberon's courses... even now, the future of software development is being led by Smalltalk whether or not the rest of the world cares to notice.

Happy Goldfish in a Bowl

Having dabbled on the edge of AI for a number of years, I enjoy the technology as well as the philosophy that surrounds the subject. Jon Udell writes of the so-called Singularity...

That's us: just goldfish to the post-human super-intelligences... True machine intelligence was what the advocates of strong AI wanted to hear about, not the amplification of human intelligence by networked computing. The problem, of course, is that we've always lacked the theoretical foundation on which to build machine intelligence. Ray Kurzweil thinks that doesn't matter, because in a decade or two we'll be able to scan brain activity with sufficient fidelity to port it by sheer brute force, without explicitly modeling the algorithms.
Now's time for this goldfish (me) to refresh himself with a healthy dose of Terry Winograd and Fernando Flores. I don't consider myself religious in the least. However I think that neither "intelligence" nor "emotions" are in any way mechanical (i.e. transferable to a machine). I do think they are *biological abstractions*. They are the names we give to our interpretation of biological (and so, chemical, and so, physical) processes.

Back to Jon on the current understanding of human vision...

We are, however, starting to sort out the higher-level architecture of these cortical columns. And it's fascinating. At each layer, signals propagate up the stack, but there's also a return path for feedback. Focusing on the structure that's connected directly to the 14x14 retinal patch, Olshausen pointed out that the amount of data fed to that structure by the retina, and passed up the column to the next layer, is dwarfed by the amount of feedback coming down from that next layer. In other words, your primary visual processor is receiving the vast majority of its input from the brain, not from the world.
We can manipulate biological and psychological processes. We can mimic them mechacinally to increasing degrees. But we cannot "make them" out of parts and we cannot "tansfer" them to such a machine. What would that mean? The simulation of the hurricane is not and never will be the hurricane even if the simulation actually destroys the city. Something destroys the city, but it is not a hurricane.

A machine that has some representation of my "brain" may continue to develop a further simulation of what my brain would be like had it undergone similar stimula. But in no way is that machine now "my brain" and in no way does that machine "feel" things in the way my "real brain" feels things. Those feelings are interpretations of abstractions of biological processes. The machine is merely a simulation of such things. If you care about me and then observe further simulations of such a machine you may further interpret your observations to be "happy" or "sad" and you may even interpret that machine to be "happy" or "sad". But that machine is in fact not happy or sad in any biological or psychological sense.

Let's face it, even my dog "loves" me because I feed it, and when it comes down to it my kids do too. We are abstract interpreters of biological processes. One interpretation of that may be "loneliness" but so? Here is where I note that my dog gets as excited to go out and pee as it does to see me come home from a week on the road. Fortunately my kids have a finer scale of excitement.

Back to Jon for more about augmentation rather than "strong" AI...

I had the rare privilege of meeting Doug Engelbart. I'd listened to his talk at the 2004 version of this conference, by way of ITConversations.com, and was deeply inspired by it. I knew he'd invented the mouse, and had helped bring GUIs and hypertext into the world, but I didn't fully appreciate the vision behind all that: networked collaboration as our first, last, and perhaps only line of defense against the perils that threaten our survival. While we're waiting around for the singularity, learning how to collaborate at planetary scale -- as Doug Engelbart saw long ago, and as I believe we are now starting to get the hang of -- seems like a really good idea.
Seems like a really good idea. "Strong" AI is fascinating, but "augmentation" is useful.

Streamlined Concurrency Modeling

I like this book Blaine refers to. It's been sitting on my shelf for a couple of years where I've picked it up and dusted off a few pages here and there. Recently I have been following it a bit in practicing *concurrent* programming as opposed to object programming per se.

Concurrent processes can be seen as "active objects". Not every object in your system should be concurrent (not even in a concurrent programming language like Oz, Erlang, or Gambit Scheme). But the significant ones almost certainly should.

An active object (concurrent process) in these systems are like smallish databases and application-specific protocols for accessing them. Each process has state and essentially implements a loop of selecting the next most important message, interpreting it, and updating its state (its little possibly-persistent "database"). These message-passing protocols are not unlike the protocols of messages sent to (sequential) objects.

More later. If you have any favorite references for concurrent programming leave a comment.

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About Me

Portland, Oregon, United States
I'm usually writing from my favorite location on the planet, the pacific northwest of the u.s. I write for myself only and unless otherwise specified my posts here should not be taken as representing an official position of my employer. Contact me at my gee mail account, username patrickdlogan.