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> ...now that the low hanging fruit has long gone. That begs the question of what we determine to be low-hanging fruit. An engineer in 2030 may look back on th

> ...now that the low hanging fruit has long gone. That begs the question of what we determine to be low-hanging fruit. An engineer in 2030 may look back on the time now and see the 2016 advancements as 'low-hanging fruit' relative to their time. Unless you think there's not much of a future in chip fabrication (in which case, you may want to tell Intel). As I see it, Moore's Law is a rough metric coined by someone almost half a century ago. Just because the metric is no longer relevant, that doesn't mean the increase in complexity is slowing.

redcalx 11y ago
The other factor here is that the increase in up-front development and fabrication plant costs has been absorbed by economies of scale, i.e. the semiconductor market has grown massively in recent years, and it's debatable how much further it can grow. Without that growth there is a natural limit to how much money gets spent on each new fab plant required for each fabrication phase.
mikehollinger 11y ago
There's another point, however. Moore's law is the basic premise around which a lot of the economy is now built. We design systems and software knowing that a predictable efficiency will be gained in X months. This is important to both back end and front end compute. For example, when the largest data centers in the world (e.g. Amazon) roll in a new series of hardware, we expect that the cost of X resources should be cheaper in 12 months compared to today. On the front end, as we figure out what makes a phone more "sticky" we expect that battery life must continue to increase, despite the fact that the device is now always listening, always recording our steps and activity, in constant contact with a radio base station thousands of feet away, and has the same number of pixels as an HDTV, which itself is now obsolete when compared to 4K displays. One of the points of the original article is that this continued increase in efficiency can continue (and therefore the Intel business model can continue to be viable). They're having no to throw a supercomputer at the problem, among other things, however.
EvanPlaice 11y ago
> ...now that the low hanging fruit has long gone. I'd postulate that the low hanging fruit came in two forms. The first being advances in general purpose CPUs by increasing the number of transistor. So, we're about to hit the hard limit in that regard. The second, being the design of software under the assumption that CPU speed will continue to increase linearly. ----- Hardware: Currently, the majority of systems architectures are designed to be general purpose. The exceptions being GPUs for parallel processing and ASIC for specialized tasks like encoding/decoding media formats. The next generation under currently under development is SoC (Systems on a Chip). Ie SoC is the complete hardware infrastructure contained on a single chip. They run cooler, are more power efficient, and are faster in terms of passing data via the internal cache layers. What may come after is a combination of SoC and dynamically configurable hardware architecture similar to how FPGAs work today. The combination of the cloud gaining mass appeal as well as IoT taking root (despite all the hype), a market will grow for chips with a combination of very predictable performance characteristics and specialized capabilities. With dynamically configurable hardware you could bootstrap a system and tell it to specialize as a graph database node, a media encoding/decoding cluster node, a Smart TV platform, a smart car CPU, etc. There's already talk of neuromorphic chips that can dynamically change/adapt to a specific environment. The other direction I see room for growth is communication speed. I've heard some about using optics as a communication bus on multi-layered chips. Material manufacturing seems to be the issue. If somebody were to come up with a solution then enabling on board optical communication busses could have a huge impact on IO performance/latency. ----- Software: We're at the tail end of 3 decades of unrestricted software glut. Every system commonly available today runs on a general purpose monolithic architecture. With a ton of legacy glut and a huge surface attack surface for security vulnerabilities. General purpose OSes won't go away for personal workstations but there's a lot of room for improvement when it comes to special purpose platforms. I've already been mocked on twitter for it but I think Unikernels will be the next major advancement in software for non-general-purpose systems. Instead of installing a huge bloated software platform and configuring it to run your code. The OS will be reduced in size to the point where it can be versioned in source control and setup as a step in the build process. NodeOS is one example of this. It uses a very tiny Linux kernel stripped of everything except the absolutely bare minimum foundation. It has a scheduler, dynamic memory management, enough of a HAL to run on a VM, and a basic network stack. Everything else runs on the V8 VM, including POSIX utility equivalents written in JS. That's just Node. There are unikernels for a wide range of different languages. There's even the Runtime.js project which is working to implement even the underlying kernel from scratch in pure JS. The Raspberry PI platform has proven beyond a reasonable doubt that there's a gaping middle ground (and potential market) between embedded programming and general purpose platforms. I think the greatest potential for future performance gains will come from cutting out the old cruft and optimizing on what we use today.

redcalx 11y ago

The other factor here is that the increase in up-front development and fabrication plant costs has been absorbed by economies of scale, i.e. the semiconductor market has grown massively in recent years, and it's debatable how much further it can grow. Without that growth there is a natural limit to how much money gets spent on each new fab plant required for each fabrication phase.

mikehollinger 11y ago

There's another point, however. Moore's law is the basic premise around which a lot of the economy is now built. We design systems and software knowing that a predictable efficiency will be gained in X months. This is important to both back end and front end compute. For example, when the largest data centers in the world (e.g. Amazon) roll in a new series of hardware, we expect that the cost of X resources should be cheaper in 12 months compared to today. On the front end, as we figure out what makes a phone more "sticky" we expect that battery life must continue to increase, despite the fact that the device is now always listening, always recording our steps and activity, in constant contact with a radio base station thousands of feet away, and has the same number of pixels as an HDTV, which itself is now obsolete when compared to 4K displays. One of the points of the original article is that this continued increase in efficiency can continue (and therefore the Intel business model can continue to be viable). They're having no to throw a supercomputer at the problem, among other things, however.

EvanPlaice 11y ago

> ...now that the low hanging fruit has long gone. I'd postulate that the low hanging fruit came in two forms. The first being advances in general purpose CPUs by increasing the number of transistor. So, we're about to hit the hard limit in that regard. The second, being the design of software under the assumption that CPU speed will continue to increase linearly. ----- Hardware: Currently, the majority of systems architectures are designed to be general purpose. The exceptions being GPUs for parallel processing and ASIC for specialized tasks like encoding/decoding media formats. The next generation under currently under development is SoC (Systems on a Chip). Ie SoC is the complete hardware infrastructure contained on a single chip. They run cooler, are more power efficient, and are faster in terms of passing data via the internal cache layers. What may come after is a combination of SoC and dynamically configurable hardware architecture similar to how FPGAs work today. The combination of the cloud gaining mass appeal as well as IoT taking root (despite all the hype), a market will grow for chips with a combination of very predictable performance characteristics and specialized capabilities. With dynamically configurable hardware you could bootstrap a system and tell it to specialize as a graph database node, a media encoding/decoding cluster node, a Smart TV platform, a smart car CPU, etc. There's already talk of neuromorphic chips that can dynamically change/adapt to a specific environment. The other direction I see room for growth is communication speed. I've heard some about using optics as a communication bus on multi-layered chips. Material manufacturing seems to be the issue. If somebody were to come up with a solution then enabling on board optical communication busses could have a huge impact on IO performance/latency. ----- Software: We're at the tail end of 3 decades of unrestricted software glut. Every system commonly available today runs on a general purpose monolithic architecture. With a ton of legacy glut and a huge surface attack surface for security vulnerabilities. General purpose OSes won't go away for personal workstations but there's a lot of room for improvement when it comes to special purpose platforms. I've already been mocked on twitter for it but I think Unikernels will be the next major advancement in software for non-general-purpose systems. Instead of installing a huge bloated software platform and configuring it to run your code. The OS will be reduced in size to the point where it can be versioned in source control and setup as a step in the build process. NodeOS is one example of this. It uses a very tiny Linux kernel stripped of everything except the absolutely bare minimum foundation. It has a scheduler, dynamic memory management, enough of a HAL to run on a VM, and a basic network stack. Everything else runs on the V8 VM, including POSIX utility equivalents written in JS. That's just Node. There are unikernels for a wide range of different languages. There's even the Runtime.js project which is working to implement even the underlying kernel from scratch in pure JS. The Raspberry PI platform has proven beyond a reasonable doubt that there's a gaping middle ground (and potential market) between embedded programming and general purpose platforms. I think the greatest potential for future performance gains will come from cutting out the old cruft and optimizing on what we use today.