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Comment by ericjang | Hacker News Reader

NVIDIA is making a big bet on GPUs being the right abstraction layer for research/production, and is nearly pivoting the entire company around this. The software/developer tools layer is really important too. Custom AI chip makers (e.g. Nervana) hope to compete with NVIDIA despite having fewer resources. What are your thoughts on how a small AI chip company can best NVIDIA/other competitors?

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We compete with them on efficiency. On a self driving car, a 1000W machine for 3d lidar data crunching isn't really feasible. If we can provide that at 10W,which we are aiming for, then we have a selling point.

As for our training chips, without divulging too much on a public forum (I'd be happy to talk more in private or over email), I think we provide the right level of abstraction and precision which would allow a researcher to one click port a tensorflow Model (we plan to support a few others like Caffe, torch, mxnet, etc out of the gate as well) to our chips.

How does 1000W compare to the rest of the car? Also, I can't find any concrete numbers from NVIDIA, but the great discussion on https://news.ycombinator.com/item?id=12938016 pointed at an Anandtech article suggesting the full Drive PX2 is 250W (and suggested that a Model S chews up about 3600W).

For reference, a reasonably big alternator on a mid-2000 petrol car is ~2200 W. Alternators are perhaps getting bigger as we stuff more electronics into cars?

That 3600 W for the Model S sounds high if I understand it's just for the brainbox; that alone would consume all your 85 kWh in less than 24h.

I'm aware (excruciatingly aware...) of that. Our numbers are ~10X better despite a process disadvantage.

And as always, Nvidia is twiddling the numbers, they exclude the cost of memory access when calculating 1 top/w, whereas we include it.

Internal combustion engines vent tens of kilowatts of waste heat to atmosphere.

Dealing with a few hundred watts more isn't a deal breaker.

Cooling 1000W of electronics in a vehicle is a tough problem. I don't know why you'd think it's easy.

Because most vehicles have a pressurised liquid cooling heat transfer system bolted in at the factory and a refrigerant cooling system.

HVAC in automotive and industrial machines is a solved problem. I don't know why you would think otherwise.

Because it's not a solved problem.

Could have fooled me. I work with industrial machines and kilowatts of electronics, it's all fairly low maintenance.

1000 watt isn't really that much heat to deal with.

Just to be clear I understand, in the car, you only need to run the forward pass, right? One frame of data at a time through the network, get the result, pass it on. The 1000W machine would be more likely used for training on large datasets, no? Aren't these different platforms for different purposes?

I hate to bring this to your attention but Nvidia is not pushing to use their full desktop GPUs in the car. In fact they have a system specially designed for use in cars which they "claim" (I have not scrutinized the numbers) is extremely efficient on a power per watt basis (AKA Nvidia DRIVE PX2). I'd keep an eye on this platform myself.

Like they don't know.

It's ok, as long as their investors don't know ;)

Copy pasting my comment from below:

I'm aware (excruciatingly aware...) of that. Our numbers are ~10X better despite a process disadvantage. And as always, Nvidia is twiddling the numbers, they exclude the cost of memory access when calculating 1 top/w, whereas we include it.

I expected that 1kW would be a drop in the bucket for a car, since moving that huge hunk of metal from A to B seems like it should totally dominate. But I worked it from first principles, and sanity checked against Tesla anecdotes [0]. At usual speeds and 2.5-3 mi/kWh [0], that's a power consumption in the tens of kW [1], so call 1kW a 5% bump. According to CNN[2], that could be around ~$20/mo from super rough back-of-the-envelope math.

If that estimate is on the money or high, I'd totally pay <= $20/mo for my car to drive itself. If it's low, I probably wouldn't pay $100+/mo for it.

[0] https://forums.tesla.com/forum/forums/miles-kwh

[1] X mph / (Y mi / kWh) = X/Y kW

[2] http://money.cnn.com/2011/05/05/news/economy/gas_prices_inco...

You might be willing to pay $20/mo, but how much do you think Tesla would be willing to pay to increase their range by 5%?

I wrote out the numbers I worked out for a tesla, but I had also done it from basic physics (plus referenced efficiencies) for a gas car, and it's not horribly different. I didn't include it because I have no idea what so ever how big of a deal adding in a 1kW power system to a gas car that still drew power from the gas engine, or what the losses look like. The order of magnitude remains about the same. I drive a prius, and if my estimate is close enough, the range isn't a factor for cars like mine. I was mostly curious in order of magnitude kW stuff, and only tangentially $ stuff.

Also consider whatever you value your hourly rate. You can work/do whatever you want for an extra hour in a driverless car on your way to work but you cant do that in a traditional car. There are other cost factors here besides electricity/gas.

So you put extra 1kW heater somewhere in the car. Now how much energy you spend on cooling?

Internal combustion engines are 20-45% efficient. That means a 150 hp car dissipates 55 KW at peak. Assuming half load that's over 25 KW to dissipate continuously. Cars usually dissipate heat by way of a ~100 kg radiator, ram air and a couple of 20W fans. Brakes dissipate far larger amounts of heat in short bursts, and are passively cooled by ram air. For EVs, I'm not sure, but I think 100KW li-ion pack will continuously emit something between 1-5KW in heat when charging or discharging.

1KW is a small fraction of a typical car's heat budget.

I agree with your general point, but to sanity check your numbers: car radiators don't even weigh a tenth of that. The entire cooling system, including fluid, is in the sub-20kg range. The entire drivetrain of a common 4-banger is in the 150-160 kilo range.

Except it only takes about 20hp to keep a car at highway speed. The rest is for acceleration, hills, headwinds and looking cool.

Driving autonomously is pretty cool don't you think...

So the first self-driving car should be a 20hp Volkswagen with a computer under the hood.

... I'd buy it!

Well, in a world where all the cars were automated and could talk to each other (coordinated merges, for instance), you'd probably be fine with 60 hp motors. Where all the vehicles are hybrid, 30 might be enough for highways.

Hilly neighborhoods might be something else entirely.

The brain can drive a car and uses a fraction of that amount of energy.

"On a self driving car, a 1000W machine for 3d lidar data crunching isn't really feasible."

How-so? That's 1.34 horsepower. Even assuming catastrophic losses in converting fuel to electrical power, say 90%, that's only 13.4 horsepower to generate 1000W.

Electrical car. You lose a lot of power like that. That translates into less range, and that's before you start redirecting air to cool it which will eat up even more range.

would love to learn more whats your email and company

If you don't mind me using my personal email, sixsamuraisoldier[at]gmail[dot]com will work

For self-driving cars in motion you don't need a monster GPU - the hard part of training is where you need a supercomputer; the "in driving" requirements are mostly about making a prediction in a short time on a pre-trained network (if you use deep learning). As for LiDAR, you reduce scanning radius to distance you can handle in realtime.

Clearly you've never run any of the object detection nets. State of the art is still 70 fps on Pascal for a 300x300 image.

I'm unaware of what else can run a 3D Wide-ResNet on lidar data at 480FPS. If you do find something like that, let me know!

Nervana was acquired by the 800 lbs gorrila of Silicon: intel

AMD has announced a major AI initiative, MIopen.

My point is that all the big chip players are entering this battle. Going to be tough for any small player to make a dent.

Nervana is a strong competitor, true. No comments on that.

MIopen however is basically just a rebranded Fiji/Polaris/Vega

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