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Can someone ELI5 this to me? I am not a hardware expert but am a programmer.

by mikek 9y ago

jacquesm 9y ago
I highly doubt there is a way to explain this as if you're five. But the very short version of it is that if you need a lot of very large FPGAs for a short while or right now then Amazon will now rent them (up to 8 in one box) to you in an environment that you hopefully are already familiar with. There are some (obvious) limitations, you're not going to be accessing the i/o pins directly but you'll be able to access all of the internal logic and a bunch of memory to create custom co-processors and other nifty stuff without breaking the bank. I can't find a price, but it won't be cheap and if you're just going to toy around with FPGA's you're better of buying one of the small kits. Here is a good primer on these: https://aws.amazon.com/ec2/instance-types/f1/ https://aws.amazon.com/ec2/instance-types/f1/ Even though you program an FPGA it is not the same as programming a processor, the 'software' tells the FPGA what to be, not what to run. Huge difference, and as a programmer you're initially going to be about as comfortable as a fish on dry land.
GrumpyYoungMan 9y ago
ELI5, hmmm? Okay, I'll take a stab at it. For some types of processing, it's vastly more efficient to implement specially-designed digital circuits to do the work instead of using a regular CPU. If the need is high-volume enough, these can be fabricated on custom silicon chips. Common examples are DSPs, GPUs, and custom Bitcoin mining chips. For low-volume applications where it's not cost efficient to fabricate custom chips, there's a specialized type of "generic" chip known as a field-programmable gate array or FPGA. These FPGAs contain a grid of digital logic gates (to oversimplify a bit) and programmable interconnections that allow them to be configured to create any type of digital circuit. While it can't run as fast as a fully custom silicon chip, it's still fast enough to get a tremendous speedup where a custom digital circuit design is beneficial. Now that Amazon has made EC2 instances with FPGA accelerator cards available, ordinary users with the need for these custom digital circuits now have access to these specialized devices without having to make the enormous upfront cash investment of purchasing and operating servers with these FPGA accelerator cards themselves. Addendum: It's also worth noting that, as Moore's law slowly grinds to a halt, that building custom digital circuits using FPGAs for specific processing needs is one of the few promising ways remaining for getting a big boost in compute-intensive app performance in the future. By making these available to a wide audience, Amazon is effectively accelerating the speed at which this type of technology will make it to ordinary desktop computing.
- jononor 9y ago
  The primary competitor for FPGAs at the moment is not so much CPUs as GPUs. Will be interesting to see what kind of systems will end up using FPGAs in datacenters. Low-latency inference using neural networks could be one. Especially if the practice of "quantizing" the networks (using <32bit integers) as Google does with their TF chips take off.

Can someone ELI5 this to me? I am not a hardware expert but am a programmer.

by mikek 9y ago

Can someone ELI5 this to me? I am not a hardware expert but am a programmer.

I highly doubt there is a way to explain this as if you're five. But the very short version of it is that if you need a lot of very large FPGAs for a short while or right now then Amazon will now rent them (up to 8 in one box) to you in an environment that you hopefully are already familiar with. There are some (obvious) limitations, you're not going to be accessing the i/o pins directly but you'll be able to access all of the internal logic and a bunch of memory to create custom co-processors and other nifty stuff without breaking the bank. I can't find a price, but it won't be cheap and if you're just going to toy around with FPGA's you're better of buying one of the small kits. Here is a good primer on these: https://aws.amazon.com/ec2/instance-types/f1/ https://aws.amazon.com/ec2/instance-types/f1/ Even though you program an FPGA it is not the same as programming a processor, the 'software' tells the FPGA what to be, not what to run. Huge difference, and as a programmer you're initially going to be about as comfortable as a fish on dry land.

GrumpyYoungMan 9y ago

ELI5, hmmm? Okay, I'll take a stab at it. For some types of processing, it's vastly more efficient to implement specially-designed digital circuits to do the work instead of using a regular CPU. If the need is high-volume enough, these can be fabricated on custom silicon chips. Common examples are DSPs, GPUs, and custom Bitcoin mining chips. For low-volume applications where it's not cost efficient to fabricate custom chips, there's a specialized type of "generic" chip known as a field-programmable gate array or FPGA. These FPGAs contain a grid of digital logic gates (to oversimplify a bit) and programmable interconnections that allow them to be configured to create any type of digital circuit. While it can't run as fast as a fully custom silicon chip, it's still fast enough to get a tremendous speedup where a custom digital circuit design is beneficial. Now that Amazon has made EC2 instances with FPGA accelerator cards available, ordinary users with the need for these custom digital circuits now have access to these specialized devices without having to make the enormous upfront cash investment of purchasing and operating servers with these FPGA accelerator cards themselves. Addendum: It's also worth noting that, as Moore's law slowly grinds to a halt, that building custom digital circuits using FPGAs for specific processing needs is one of the few promising ways remaining for getting a big boost in compute-intensive app performance in the future. By making these available to a wide audience, Amazon is effectively accelerating the speed at which this type of technology will make it to ordinary desktop computing.

jononor 9y ago
The primary competitor for FPGAs at the moment is not so much CPUs as GPUs. Will be interesting to see what kind of systems will end up using FPGAs in datacenters. Low-latency inference using neural networks could be one. Especially if the practice of "quantizing" the networks (using <32bit integers) as Google does with their TF chips take off.