The Future of Hardware Is Software
octoml.ai
The Future of Hardware Is Software
1–10 of 35 posts
Re: The Future of Hardware Is Software
#2"The Future of Hardware Is Software" ... says everyone that wants to sell you AI software on commoditized hardware.
Yet here I am, I recently won an AI competition by reviving an old 2005 algorithm and just using the fact that compute power has 7000x-ed since then (from 5 GFLOPS on a P4 to 35 TFLOPS on a 3090). No AI was needed.
And now I'm building custom electronics for a new type of 3D camera because even after years of AI and deep learning research, structured light and/or stereoscopic 3D depth estimation is still unusable. Try training a NERF from "only" 3 UHD images and you know what I mean.
Re: The Future of Hardware Is Software
#3"The Future of Hardware Is Software" ... says everyone that wants to sell you AI software on commoditized hardware. Yet here I am, I recently won an AI competition by reviving an old 2005 algorithm and just using the fact that compute power has 7000x-ed since then (from 5 GFLOPS on a P4 to 35 TFLOPS on a 3090). No AI was needed. And now I'm building custom electronics for a new type of 3D camera because even after ye…
> I'm building custom electronics for a new type of 3D camera
I would love to know more. I am working on an open source farming robot and vision is an important component. Are you able to share more?
Re: The Future of Hardware Is Software
#4"The Future of Hardware Is Software" ... says everyone that wants to sell you AI software on commoditized hardware. Yet here I am, I recently won an AI competition by reviving an old 2005 algorithm and just using the fact that compute power has 7000x-ed since then (from 5 GFLOPS on a P4 to 35 TFLOPS on a 3090). No AI was needed. And now I'm building custom electronics for a new type of 3D camera because even after ye…
[deleted]
Re: The Future of Hardware Is Software
#5"The Future of Hardware Is Software" ... says everyone that wants to sell you AI software on commoditized hardware. Yet here I am, I recently won an AI competition by reviving an old 2005 algorithm and just using the fact that compute power has 7000x-ed since then (from 5 GFLOPS on a P4 to 35 TFLOPS on a 3090). No AI was needed. And now I'm building custom electronics for a new type of 3D camera because even after ye…
You're such a tease!
Seriously, please share the deets on this 2005 "junker" algo.
It was super unsatisfying to read your post with so much interesting information glossed over.
Re: The Future of Hardware Is Software
#6> A classic example is Itanium: it is only a historical footnote today, but Itanium’s explicit parallelism and focus on scalability once made it look like the future of CPUs. The problem was never the hardware itself—it was difficult compilation and backward compatibility with the x86 software ecosystem that doomed Itanium.
The problem with the Itanium was the hardware itself. Finding sufficient ILP on general purpose loads for a VLIW like Itanium is an unsolved problem in compiler design. Saying the problem with Itanium was software would be like entering a drag-racer in formula 1 and saying the problem was that the drivers weren't good enough at steering.
Re: The Future of Hardware Is Software
#7> A classic example is Itanium: it is only a historical footnote today, but Itanium’s explicit parallelism and focus on scalability once made it look like the future of CPUs. The problem was never the hardware itself—it was difficult compilation and backward compatibility with the x86 software ecosystem that doomed Itanium. The problem with the Itanium was the hardware itself. Finding sufficient ILP on general purpos…
There are a lot of important numerical algorithms which would have really benefited if Itanium had gone through iteration and growth. A mainstream VLIW could've had it's place, and it's trivial to find parallelism in FFTs, SVDs, matrix multiplies, and so on.
To me, there is a spectrum of parallelism on the desktop:
multi-server,
multi-process,
multi-threaded (shared mem),
,
SIMD instructions
I think it's a shame Itanium failed, and I think it failed for the wrong reasons. At the time, I remember everyone criticizing it for not running legacy x86 applications very well. As though word processor, spreadsheet, and presentation software wasn't fast enough. Saying legacy apps in existing languages don't make it easy to find the ILP seems like a slight generalization of that.
The AMD64 ISA (which is what really killed Itanium) was a blessing and a curse. It made x86 just better enough to not be awful, but it killed desktop/server alternatives for at least 25 years. Maybe ARM will make inroads, but it isn't that much better either.
Re: The Future of Hardware Is Software
#8You remember the modular phone where you can replace parts and not replace everything when you want to update your phone? This hardware failure tells you that you need to use the latest hardware to run the latest software.
Re: The Future of Hardware Is Software
#9> A classic example is Itanium: it is only a historical footnote today, but Itanium’s explicit parallelism and focus on scalability once made it look like the future of CPUs. The problem was never the hardware itself—it was difficult compilation and backward compatibility with the x86 software ecosystem that doomed Itanium. The problem with the Itanium was the hardware itself. Finding sufficient ILP on general purpos…
There are a lot of important numerical algorithms which would have really benefited if Itanium had gone through iteration and growth. A mainstream VLIW could've had it's place, and it's trivial to find parallelism in FFTs, SVDs, matrix multiplies, and so on. To me, there is a spectrum of parallelism on the desktop: multi-server, multi-process, multi-threaded (shared mem), , SIMD instructions Yeah, Itanium might have…
> There are a lot of important numerical algorithms which would have really benefited if Itanium had gone through iteration and growth. A mainstream VLIW could've had it's place, and it's trivial to find parallelism in FFTs, SVDs, matrix multiplies, and so on.
DSPs (which have great perf/watt for the numerical algorithms you mention) have used VLIW for decades, so of course there is a place for it. GPUs have moved in for all of those operations at this point though. The bet with Itanium was that compilers could be made sufficiently smart to make VLIW work for non-numeric workloads, and that bet failed to pay off. Intel and HP had hundreds of smart people trying to solve the "software problem" of Itanium and they did not succeed.
> I think it's a shame Itanium failed, and I think it failed for the wrong reasons. At the time, I remember everyone criticizing it for not running legacy x86 applications very well. As though word processor, spreadsheet, and presentation software wasn't fast enough. Saying legacy apps in existing languages don't make it easy to find the ILP seems like a slight generalization of that.
Desktop applications is a red-herring given that Itanium was targeted primarily at the workstation and server market. There was also a bad-timing issue as it was at about the same time that PC hardware was displacing dedicated workstations and server hardware.
Re: The Future of Hardware Is Software
#10> A classic example is Itanium: it is only a historical footnote today, but Itanium’s explicit parallelism and focus on scalability once made it look like the future of CPUs. The problem was never the hardware itself—it was difficult compilation and backward compatibility with the x86 software ecosystem that doomed Itanium. The problem with the Itanium was the hardware itself. Finding sufficient ILP on general purpos…
There are a lot of important numerical algorithms which would have really benefited if Itanium had gone through iteration and growth. A mainstream VLIW could've had it's place, and it's trivial to find parallelism in FFTs, SVDs, matrix multiplies, and so on. To me, there is a spectrum of parallelism on the desktop: multi-server, multi-process, multi-threaded (shared mem), , SIMD instructions Yeah, Itanium might have…
>A mainstream VLIW could've had it's place, and it's trivial to find parallelism in FFTs, SVDs, matrix multiplies, and so on.
There are already DSPs for this purpose, but typical server workloads don't generally use those algorithms. Perhaps Itanium would have made a good DSP but it wasn't really aimed at that market.