5 ms·

If I was Intel, I would be going straight for the TPU market. GPU have a bunch of legacy from the G=Graphics legacy. The real money maker is not likely to be ga

If I was Intel, I would be going straight for the TPU market. GPU have a bunch of legacy from the G=Graphics legacy. The real money maker is not likely to be gamers (although it has been healthy enough market). The future of those vector processing monsters is going to be ML (and maybe crypto). This is the difference between attempting to leapfrog compared to trying to catch up.

rrss 6y ago
This is what they tried to do with Nervana and are trying again to do with Habana.
alpha_squared 6y ago
> The future of those vector processing monsters is going to be ML (and maybe crypto) That's a heavy bet on ML and crypto(-currency? -graphy?). Has ML, so far, really made any industry-changing inroads in any industry? I'm not entirely discounting the value of ML or crypto, just questioning the premature hype train that exists in tech circles (especially HN).
- orf 6y ago
  > Has ML, so far, really made any industry-changing inroads in any industry? Does the tech industry not count, or are you only considering industries that are typically slower moving?
  - ocdtrekkie 6y ago
    The tech industry claims it applies machine learning all over the place, but I doubt it actually moves the needle much.
    - orf 6y ago
      Is that opinion based on anything firmer than a pessimistic outlook? Lots of people jump on any trend, it doesn't mean the hype is unjustified or that nobody is "moving the needle" with that trend. Recommendations (e-commerce, advertising, music, etc) have been pretty revolutionized by it.
      - alpha_squared 6y ago
        > Recommendations (e-commerce, advertising, music, etc) have been pretty revolutionized by it. I'd like to learn more about how they've been revolutionized by it. Any sources you could share?
      - InitialLastName 6y ago
        As a personal anecdote, the quality of the recommendations I receive across the board has been roughly inversely proportional to the level hype around ML in the tech press and academia. C.f. Youtube's, Amazon and Netflix (products that bet BIG on recommendations) being incapable of recommending compelling material.
    - exged 6y ago
      ML contributes to a significant fraction of revenue at three of the world's largest companies (Amazon, Google, Facebook - largely through recommendations and ad ranking). It also drives numerous features that other tech companies build into their products to stay competitive (think FaceID on iPhone). Hard to argue that it doesn't move the needle...
- deleted 6y ago
  [deleted]
- reggieband 6y ago
  >That's a heavy bet on ML and crypto Well, yes that is the point. My theory is that the gaming market for GPUs is well understood. I don't think there are any lurking surprises on the number of new gamers buying high-end PCs (or mobile devices with hefty graphics capabilities) in the foreseeable future. However, if one or more of the multitude of new start-ups entering the ML and crypto (-currency) space end up being the next Amazon/Google/Facebook then that would be both unforeseeable and unbelievably transformative. Maybe it won't happen (that is the risk) but my intuition suggests something is going to come out of that work. I mean, it didn't work out for Sony when they threw a bunch of SPUs in the PS3. They went back to a traditional design for their next two consoles. So not every risk pans out!
- nordsieck 6y ago
  > crypto(-currency? -graphy?) TPUs are massively parallel Float16 engines - not really applicable to anything outside of ML.
- RantyDave 6y ago
  > Has ML, so far, really made any industry-changing inroads in any industry? It is (IIRC) a pretty fundamental part of self driving tech. I honestly think this is what drives a lot of Nvidia's valuation.
- nemothekid 6y ago
  nvidia's largest revenue driver, gaming, made 1.4B dollars last year (up 56% YoY). nvidia's second largest, "data center" (AI) made 968M (up 43% YoY). Other revenue was 661M. Up to you if nvidia's second largest revenue center, of nearly a billion/year is "industry changing"
- nine_k 6y ago
  A ton. Look at the nearest device around you, chances are it runs Siri, Alexa, Cortana, or Google voice assistant. This will only grow. Same with machine vision. It's going to be everywhere — not just self-driving trucks (which, unlike cars, are going yo be big soon), but also security devices, warehouse automation, etc. All this is normally run on vector / tensor processors, both in huge datacenters and on local beefy devices (where a stock built-in GPU alongside ARM cores is not cutting it). This is a growing market with.a lot of potential. Licensing CUDA could be quite a hassle, though. OpenCL is open but less widely used.
KMag 6y ago
> The future of those vector processing monsters is going to be ML (and maybe crypto). Hopefully some of those cryptocurrencies (until they get proof-of-stake fully worked out) move to memory-hard proof-of-work using Curve25519, Ring Learning With Errors (New Hope), and ChaCha20-Poly1309, so cryptocurrency accelerators can pull double-duty as quantum-resistant TLS accelerators. I'm not necessarily meaning dedicated instructions, but things like vectorized add, xor, and shift/rotate instructions, at least 53 bit x 53 bit -> 106 bit integer multiplies (more likely 64 x 64 -> 128), and other somewhat generic operations that tend to be useful in modern cryptography.
gumby 6y ago
They have. Their first purchase (Nervana) hasn’t worked out for them so they are now working through their purchase of the more conventional Habana.
marcosdumay 6y ago
The one thing I don't get is, there are a lot of machines out there that would gain a lot from specialized search hardware (think about Prolog acceleration engines, but lower level). For a start, every database server (SQL or NoSQL) would benefit. It is also hardware that is similar to ML acceleration, it needs better integer and boolean (algebra, not branching) support, and has a stronger focus on memory access (that ML acceleration also needs, but gains less from). So how comes nobody even speak about this?
- imtringued 6y ago
  I don't understand how database servers would benefit. You would have to add the search hardware directly to DRAM for any meaningful gains.
  - marcosdumay 6y ago
    You would need large memory bandwidth and a good set of cache pre-population heuristics (putting it directly on the memory is a way to get the bandwidth). ML would benefit from both too, as would highly complex graphics and physics simulation. The cache pre-population is probably at odds with low latency graphics.
shaklee3 6y ago
Intel did go for the tpu market. It was called the nervana chip, and they cancelled it.

rrss 6y ago

This is what they tried to do with Nervana and are trying again to do with Habana.

alpha_squared 6y ago

> The future of those vector processing monsters is going to be ML (and maybe crypto) That's a heavy bet on ML and crypto(-currency? -graphy?). Has ML, so far, really made any industry-changing inroads in any industry? I'm not entirely discounting the value of ML or crypto, just questioning the premature hype train that exists in tech circles (especially HN).

orf 6y ago
> Has ML, so far, really made any industry-changing inroads in any industry? Does the tech industry not count, or are you only considering industries that are typically slower moving?
- ocdtrekkie 6y ago
  The tech industry claims it applies machine learning all over the place, but I doubt it actually moves the needle much.
  - orf 6y ago
    Is that opinion based on anything firmer than a pessimistic outlook? Lots of people jump on any trend, it doesn't mean the hype is unjustified or that nobody is "moving the needle" with that trend. Recommendations (e-commerce, advertising, music, etc) have been pretty revolutionized by it.
    - alpha_squared 6y ago
      > Recommendations (e-commerce, advertising, music, etc) have been pretty revolutionized by it. I'd like to learn more about how they've been revolutionized by it. Any sources you could share?
    - InitialLastName 6y ago
      As a personal anecdote, the quality of the recommendations I receive across the board has been roughly inversely proportional to the level hype around ML in the tech press and academia. C.f. Youtube's, Amazon and Netflix (products that bet BIG on recommendations) being incapable of recommending compelling material.
  - exged 6y ago
    ML contributes to a significant fraction of revenue at three of the world's largest companies (Amazon, Google, Facebook - largely through recommendations and ad ranking). It also drives numerous features that other tech companies build into their products to stay competitive (think FaceID on iPhone). Hard to argue that it doesn't move the needle...
deleted 6y ago
[deleted]
reggieband 6y ago
>That's a heavy bet on ML and crypto Well, yes that is the point. My theory is that the gaming market for GPUs is well understood. I don't think there are any lurking surprises on the number of new gamers buying high-end PCs (or mobile devices with hefty graphics capabilities) in the foreseeable future. However, if one or more of the multitude of new start-ups entering the ML and crypto (-currency) space end up being the next Amazon/Google/Facebook then that would be both unforeseeable and unbelievably transformative. Maybe it won't happen (that is the risk) but my intuition suggests something is going to come out of that work. I mean, it didn't work out for Sony when they threw a bunch of SPUs in the PS3. They went back to a traditional design for their next two consoles. So not every risk pans out!
nordsieck 6y ago
> crypto(-currency? -graphy?) TPUs are massively parallel Float16 engines - not really applicable to anything outside of ML.
RantyDave 6y ago
> Has ML, so far, really made any industry-changing inroads in any industry? It is (IIRC) a pretty fundamental part of self driving tech. I honestly think this is what drives a lot of Nvidia's valuation.
nemothekid 6y ago
nvidia's largest revenue driver, gaming, made 1.4B dollars last year (up 56% YoY). nvidia's second largest, "data center" (AI) made 968M (up 43% YoY). Other revenue was 661M. Up to you if nvidia's second largest revenue center, of nearly a billion/year is "industry changing"
nine_k 6y ago
A ton. Look at the nearest device around you, chances are it runs Siri, Alexa, Cortana, or Google voice assistant. This will only grow. Same with machine vision. It's going to be everywhere — not just self-driving trucks (which, unlike cars, are going yo be big soon), but also security devices, warehouse automation, etc. All this is normally run on vector / tensor processors, both in huge datacenters and on local beefy devices (where a stock built-in GPU alongside ARM cores is not cutting it). This is a growing market with.a lot of potential. Licensing CUDA could be quite a hassle, though. OpenCL is open but less widely used.

KMag 6y ago

> The future of those vector processing monsters is going to be ML (and maybe crypto). Hopefully some of those cryptocurrencies (until they get proof-of-stake fully worked out) move to memory-hard proof-of-work using Curve25519, Ring Learning With Errors (New Hope), and ChaCha20-Poly1309, so cryptocurrency accelerators can pull double-duty as quantum-resistant TLS accelerators. I'm not necessarily meaning dedicated instructions, but things like vectorized add, xor, and shift/rotate instructions, at least 53 bit x 53 bit -> 106 bit integer multiplies (more likely 64 x 64 -> 128), and other somewhat generic operations that tend to be useful in modern cryptography.

gumby 6y ago

They have. Their first purchase (Nervana) hasn’t worked out for them so they are now working through their purchase of the more conventional Habana.

marcosdumay 6y ago

The one thing I don't get is, there are a lot of machines out there that would gain a lot from specialized search hardware (think about Prolog acceleration engines, but lower level). For a start, every database server (SQL or NoSQL) would benefit. It is also hardware that is similar to ML acceleration, it needs better integer and boolean (algebra, not branching) support, and has a stronger focus on memory access (that ML acceleration also needs, but gains less from). So how comes nobody even speak about this?

imtringued 6y ago
I don't understand how database servers would benefit. You would have to add the search hardware directly to DRAM for any meaningful gains.
- marcosdumay 6y ago
  You would need large memory bandwidth and a good set of cache pre-population heuristics (putting it directly on the memory is a way to get the bandwidth). ML would benefit from both too, as would highly complex graphics and physics simulation. The cache pre-population is probably at odds with low latency graphics.

shaklee3 6y ago

Intel did go for the tpu market. It was called the nervana chip, and they cancelled it.