Its all on Twitter man...

I was looking for a Squeezebox replacement since my device died and they stopped making it. I really didn't want to build out a dedicated PC or Raspberry solution just for audio, so was making do with Roku for audio (it acutally has a surprisingly large number of audio streaming services - it even covers my local FM radio channels).

Tried the first Chromecast - and it was largely a "meh" experience. Video was grainy and choppy and audio sounded quite substandard. For example the same youtube audio or internet audio would sound much better when streamed from the Roku channel than when casted from Chromecast.

Took another gamble at the new Chromecast Audio - and it is a phenomenal device. It actually plays as well as my Squeezebox. For $35, you get really high quality audio, and it has digital out so you can connect it to a DAC, or optionally use its inbuilt DAC which is not bad at all. Some people are even using it to drive moderately hard to drive headphones. It also supports high res audio up to 24/96. The really neat thing is that if you cast Spotify or Pandora from your phone to the CCA device, it will stream directly from Spotify after the initial handshake and will not stream through your phone. All in all, I can't imagine how they pulled off this quality of audio output and features for $35.

Ah, OK, so it is more or less the latest version of ASaP/ASaP2. I just made a post up-thread about my memory of ASaP. It looked interesting, but as you point out, it has some real practical issues.

At the time we spoke with them, it sounded like whenever you loaded an algorithm chain, you had to map it to the specific chip you were going to run it on, even, to account for bad cores, different core speeds, etc. Each core has a local oscillator. Whee...

I'm familiar with Dr. Baas' older work (ASaP and ASaP2). He presented his work to a team of processor architects I was a part of several years ago.

At least at that time (which, as I said, was several years ago), one class of algorithms they were looking at was signal processing chains, where the processing steps could be described as a directed graph of processing steps. The ASaP compiler would then decompose the computational kernels so that the compute / storage / bandwidth requirements were roughly equal in each subdivision, and then allocate nodes in the resulting, reduced graphs to processors in the array.

(By roughly equal, I mean that each core would hit its bottleneck at roughly the same time as the others whenever possible, whether it be compute or bandwidth. For storage, you were limited to the tiny memory on each processor, unless you grabbed a neighbor and used it solely for its memory.)

The actual array had a straightforward Manhattan routing scheme, where each node could talk to its neighbors, or bypass a neighbor and reach two nodes away (IIRC), with a small latency penalty. Communication was scoreboarded, so each processor ran when it had data and room in its output buffer, and would locally stall if it couldn't input or output. The graph mapping scheme was pretty flexible, and it could account for heterogenous core mixes. For example, you could have a few cores with "more expensive" operations only needed by a few stages of the algorithm. Or, interestingly, avoid bad cores, routing around them.

It was a GALS design (Globally Asynchronous, Locally Synchronous), meaning that each of the cores were running slightly different frequencies. That alone makes the cores slightly heterogeneous. IIRC, the mapping algorithm could take that into account as well. In fact, as I recall, you pretty much needed to remap your algorithm to the specific chip you had in-hand to ensure best operation.

The examples we saw included stuff familiar to the business I was in—DSP—and included stuff like WiFi router stacks, various kinds of modem processing pipelines, and I believe some video processing pipelines. The processors themselves had very little memory, and in fact some algorithms would borrow a neighboring core just for its RAM, if it needed it for intermediate results or lookup tables. I think FFT was one example, where the sine tables ended up stored in the neighbor.

That mapping technology reminds me quite a lot of synthesis technologies for FPGAs, or maybe the mapping technologies they use to compile a large design for simulation on a box like Cadence's Palladium. The big difference is granularity. Instead of lookup-table (LUT) cells, and gate-level mapping, you're operating at the level of a simple loop kernel.

Lots of interesting workloads could run on such a device, particularly if they have heterogenous compute stages. Large matrix computations aren't as interesting. They need to touch a lot of data, and they're doing the same basic operations across all the elements. So, it doesn't serve the lower levels of the machine learning/machine vision stacks well. But the middle layer, which focuses on decision-guided computation, may benefit from large numbers of nimble cores that can dynamically load balance a little better across the whole net.

I haven't read the KiloCore paper yet, but I suspect it draws on the ASaP/ASaP2 legacy. The blurb certainly reminds me of that work.

And what's funny, is about 2 days before they announced KiloCore, I was just describing Dr. Baas' work to someone else. I shouldn't have been surprised he was working on something interesting.

Came here to say the same thing. The nice thing about a compact proof is that it may generalize to other situations or offer greater insights. This is certainly not a compact proof. But, to say it's not a proof is ludicrous. It's a very explicit and detailed proof.

It's the difference between adding up the numbers 1 through 100 sequentially (perhaps by counting on your fingers even), and using Gauss' insight to take a short cut. The computer didn't take any insight-yielding shortcuts, but still got the answer.

________

(And yes, Gauss' story is probably apocryphal; but still the difference between the approaches is what I'm getting at.)

(I say "insight-yielding shortcut" to distinguish it from the many heuristics that modern SAT solvers use, including the one used here.)

$10 a month is indeed expensive when compared to Ooma. Ooma is free - all you have to do is pay for the device, which admittedly is $100. But it works well, and I have been using it for over a year without any complaints or issues. And international call rates are very reasonable too - about 6-8 cents a minute. And while $100 is a bit high, the device itself is quite sleek and well implemented. It has voicemail and recording facility, and is really easy to use and setup (took me all of 2 minutes to setup).

I do pay tax for the landline service (everyone has to) but it only amounts to about 3-4 bucks a month. I would imagine that one would have to pay the same rate or possibly higher for the Google landline service.

But yes, Vonage (which I replaced with Ooma) is indeed overpriced and not at all worth the money.

What makes you think OP was talking about a Christian god?

The kind of generation upon generation endemic poverty exists because of lack of access, lack of communication, lack of transport, lack of awareness of employment options, lack of information. Take a subsistence farmer or a contract farmer for example. He is completely dependent on rain and weather conditions to get a reasonably successful crop that will give his family just about enough calories to last the rest of the year, and a little bit of money for other survival needs. One bad crop, one bad season means that he has to take a loan from a loanshark / local moneylender at interest rates of 3-5% a week. Inevitably he will become indebted for life, and if another bad season follows, his children with either die of malnutrition or he will commit suicide by drinking pesticide. Or often both. Not necessarily in the same order.

The other big category of poverty stricken people in India are the ones that are less tied to the land. Part time laborers, the ones who work in construction sites, brick kilns, mines, public or private construction projects, etc.

In many of these categories of people, there is a very real benefit to having a cell phone and having rudimentary internet access. Even if not the internet or even wikipedia, to mesaging apps like whatsapp, weather forecasting apps, apps that display job opportunities for temp workers, daily wage laborers etc.

A subsistence farmer or a daily wage laborer could benefit enormously from access to job opportunities, access to better information about the weather, commodity prices, prices of pesticides, grains etc. Or even just the ability to message relatives and be better networked and better informed. Consider the fact that a daily wage laborer in a big city makes 10x the money than a daily wage worker in a remote inaccessible village. Not only that, the big city laborer is also employed many more days in a year.

So why does the poverty stricken villager not move to the big city? Why does the villager let his children become matchsticks? Why does the villager commit suicide even when he knows it also means a death sentence for his family? Why is he, for lack of a better word, so *dumb*? You think a charity organization that will visit his village once a decade and will give him a sack of rice will help him in any way in the long run??

Dave's argument starts with real-world numbers regarding solar insolation and PV conversion efficiency to establish a baseline. The exact details of a specific implementation won't change the broad conclusion that the energy balance alone, even if you take out the gee-whiz features of the Solar Freakin' Roadways design such as LEDs and networking, doesn't make sense.

When you add all the other stuff on top, it only gets worse.

Fundamental issues: Only so much sun hits the earth, and PV cells only convert a certain fraction to usable energy. When you mount them flat on the ground, you reduce their efficiency further because they're not perpendicular to the incoming light. When you put them under thick enough glass to support real physical loads such as cars and trucks, you lose even more. And when you distribute them over a large area, transmission losses become a Big Deal.

I'm personally skeptical you could build solar panels that would withstand actual vehicle traffic, at least the way we build roads here in the US. Real world roads aren't flat, and they change shape over time as they wear and as the road bed settles and degrades. But real world glass isn't very plastic, and won't conform to a changing surface. It's more likely to crack and break into many pieces. Likewise for the PV cells under it. You'd have to put some beefy steel plates under these to guarantee a sufficiently flat mounting surface to support the load-bearing glass.

The main source of opposition by the way is ordinary users, not corporations or telcos. The reason for the opposition is not that facebook will become a monopoly ISP. The reason is that facebook's service breaks net neutrality.

Ordinary users everywhere are fighting to preserve net neutrality, while corporations are fighting against it (for it gives them a chance to strong-arm websites and services and extort money from them).

Basic services need to be neutral. If toll roads started charging differently depending on the brand of car you are driving (because they get kickbacks from certain car manufacturers), there would be a shit-storm of controversy. And when it comes to basic services being monopolies, the irony is that the US has far worse monopolies when it comes to services like internet, cable, etc.

India has a rapidly growing startup culture, and a lot of these startups are heavily dependent on the internet for either service delivery or communication. However, if net neutrality breaks, the entry barrier for startups would be so high and cumbersome and expensive, that most of them would die.

You can talk about net neutrality being obsolete in a post internet world, etc. But the reality is that it only works in countries that have very very strong protection against monopoly abuse, so that they can guarantee that the free market works truly like a free market with a chance for everyone to try and succeed. However, this situation is already massively distorted because the big companies have become so big and rich and monopolized that small fry startups essentially pose no competition.

But heck, even in the US, with all the protection, monopolies basically do what they want.

A country like India *needs* its basic services to be open and neutral so the nascent growing companies have half a chance to succeed.

Seems like this should just affect Chrome / Chromium and anything derived from those, as it's an implementation issue in the V8 JavaScript interpreter. (V8 is the name for the engine in Chrome.)

That is, it's not a JavaScript / ECMAScript bug in the standard (as implied by the headline), but rather a bug in one company's implementation.

Compare/contrast with the comically bad PRNG enshrined in the C standard itself:

static unsigned long int next = 1;
int rand(void) // RAND_MAX assumed to be 32767
{
next = next * 1103515245 + 12345;
return (unsigned int)(next/65536) % 32768;
}

Thankfully, though, this is just an example, and not required by the standard. But, many simple C compilers use that implementation. It's got plenty of problems, such as always alternating between even and odd values. If the last value was odd, the next value is even....

Without seeing the linked site, it's hard to say what exactly the EXE was meant to accomplish. If it's some sleazoid V14GRA site, or Scan Your PC Now for Viruses site, it's pretty easy to call it malware.

Some relevant information was redacted, unfortunately.

Today, I learnt that solar panels need fertile irrigated soil to work.

Recent -K CPUs don't come with coolers as vocal enthusiasts have been telling Intel they just throw away the stock coolers and use third-party ones instead. You can buy Intel coolers separately for CPUs that aren't supplied with one.

You can buy Intel BXTS13A (air) and BXTS13X (liquid) coolers separately.