For Better Computing, Liberate CPUs from Garbage Collection

A recent custom chip project I have been a part of for basically a decade is nearing production.

Made on a fairly large, old process. Despite this, many custom features have been added. For many tasks, the performance will be competetive with much more complex, resource intensive devices. It is built in a way that allows for efficient, multi core computing, concurrent or parallel, sans an OS.

People will write those, but many will just grab the pieces they want, put them on cores, then write their target app on top. The prior version, Propeller 1, made doing that a lot easier than one might think.

What struck me was the combination of very well planned silicon, coupled with software, can really perform. It reminds me of the custom chips we saw in early computing. Amiga, SGI, many others made adapter cards to get things done.

All of that stuff nailed the tasks cold, would always perform. As CPUs got quicker, more could be move to software of course.

But now that is hard again

Software plus purpose built silicon is going to deliver peak performance.

Always has.

In that project, it took years, but a great many use cases were considered, FPGA simulations ran, code written, and then augmented with hardware, special instructions and sub systems intended to maximize performance while retaining a lot of flexibility.

The way I see it, general purpose computers may just end up back where they were before.

In 8 bit times, an Apple 2 was an all software machine. People bought and made cards to do specific things very well. Other computers had custom chips that focused on games, etc...

In the later era, Amiga, SGI made great hardware that was focused on specific things, while the PC was more like the Apple 2.

We are currently leaving a long era where general purpose computing made sense for most cases, and software got refined, things got faster, and we saw many good cycles.

Soon, more efficient CPU designs, often with well tuned instructions for given tasks may be directing a lot of purpose built silicon. Phones and tablets vs laptops give us a tiny look at one part of how it might go.

GPU instances, specialized network maybe filesystem CPUs with highly optimized instruction sets already exist.

More will come.

Many use cases can benefit from real time or just faster performance per watt. Software plus custom silicon will nail that, and it is getting easier to do.

RISC V has plans for specialized instructions baked in. It may well be that "one to bind them all", nudging out the more expensive ARM, for example. And maybe not. ARM is lean and mean and mature. Who knows?

All I know is the drive to do more per watt as well as the drive to improve peak sequential compute, because there are still too many use cases where doing that makes sense, given either the nature of the problem space, or accumulates software warrant the effort.

We are already seeing the GPU idea expanded on.

Gonna be interesting and more difficult times ahead.

For those wondering: that’s because malloc/free ‘visits’ every dead object, while garbage collection visits the live ones (another way to say that: free collects garbage, the moment it is created, GC collects non-garbage, periodically) and there typically is way more garbage than non-garbage.

I haven’t seen energy usage comparisons that include extra energy use due to GC’s higher memory usage, though. That possibly is because it is hard to quantify. On current technology, you pay for your RAM’s energy usage the moment you power it on, whether you need it or not)

Hard to say but I can't imagine why it could be faster than normal core to core communication. In that case it's equivalent to a parallel GC, right?