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General purpose CPUs can only get so good. With that said, there are still many advancements that can be made to shrink die sizes and/or shove more transistors

General purpose CPUs can only get so good. With that said, there are still many advancements that can be made to shrink die sizes and/or shove more transistors more closely together (3D is hard due to heat… but…). I’m excited about photon-based processors, but until that’s a reality we still have a ton of headway for application-specific scaling. If you rip specific loops out of a general purpose CPU, there are still plenty of gains to be made!

formerly_proven 3y ago
> General purpose CPUs can only get so good People claimed this - “single core is over” - years ago when Intel was stuck doing Skylake refreshes and AMD’s Ryzen only matched the older Haswell CPUs.
- jumploops 3y ago
  To clarify, my point was about general-purpose CPUs, not single or multi-core. A general-purpose CPU requires that a program is transformed (via compilation or interpretation) into a set of basic instructions, ones that the processor knows how to handle. This means that almost every program requires many cycles to complete, even if the underlying logic itself could theoretically be done within a single cycle (or within no cycle at all!). On the other end of the spectrum are FPGAs and ASICs, programmable or dedicated circuits that allow you to create specialized logic that corresponds directly to a specific need. Bringing this back to the discussion at hand: Moore's law cares nothing about general-purpose CPUS, and is just focused on number of transistors on an IC doubling. With that said, transistors can only get so small (due to the laws of physics), and so one can presume we'll see an end to scaling eventually. There are changes we can make to improve general-purpose CPU architecture, regardless of transistor count, and there are changes we can make to how we run programs (moving dedicated logic to dedicated circuits). Forcing any logic into a generic set of steps that run a in a loop will always be less efficient than wiring up the logic itself. The questions has always been whether to wait for the machine to get faster or to create the dedicated logic yourself. The former has been true since the beginning of computation, and has been closely associated with Moore's law. With that said, it doesn't mean that the literal end of Moore's law is the end of computational efficiency gains.

formerly_proven 3y ago

> General purpose CPUs can only get so good People claimed this - “single core is over” - years ago when Intel was stuck doing Skylake refreshes and AMD’s Ryzen only matched the older Haswell CPUs.

jumploops 3y ago
To clarify, my point was about general-purpose CPUs, not single or multi-core. A general-purpose CPU requires that a program is transformed (via compilation or interpretation) into a set of basic instructions, ones that the processor knows how to handle. This means that almost every program requires many cycles to complete, even if the underlying logic itself could theoretically be done within a single cycle (or within no cycle at all!). On the other end of the spectrum are FPGAs and ASICs, programmable or dedicated circuits that allow you to create specialized logic that corresponds directly to a specific need. Bringing this back to the discussion at hand: Moore's law cares nothing about general-purpose CPUS, and is just focused on number of transistors on an IC doubling. With that said, transistors can only get so small (due to the laws of physics), and so one can presume we'll see an end to scaling eventually. There are changes we can make to improve general-purpose CPU architecture, regardless of transistor count, and there are changes we can make to how we run programs (moving dedicated logic to dedicated circuits). Forcing any logic into a generic set of steps that run a in a loop will always be less efficient than wiring up the logic itself. The questions has always been whether to wait for the machine to get faster or to create the dedicated logic yourself. The former has been true since the beginning of computation, and has been closely associated with Moore's law. With that said, it doesn't mean that the literal end of Moore's law is the end of computational efficiency gains.