Many of us are familiar with Geekerwan for their in-depth technical analysis on silicon architecture.
Talks 8GB RAM, core counts, thermal management.
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Geekerwan interviews Johny Srouji on A18/M4
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Leave it to an Apple exec to have a 15 minute interview and not say a single thing noteworthy.
Only minor interesting bit is that the Mac GPU and iPhone GPU have small underlying differences.
Only minor interesting bit is that the Mac GPU and iPhone GPU have small underlying differences.
Yeah ... that was a little interesting ... if I had to guess, there might be a differing amount of L1 cache per GPU core between A and M-series GPUs - especially now that the amount of L1 cache is quite large. But that's just a guess.
I think he said a lot of interesting things. The questions were kind of dumb though.
Agreed. Johny kept emphasising the fact that Apple thinks of making the best product. Geekerwan kept approaching things from the specific component specification viewpoint.
It is becoming increasingly clear that companies see Chips and Cheese and Geekerwan as the successors to Anandtech. I still find it amazing that they can interview the lead architects of the most important companies.
I thought the questions/answers were both fine, yes a touch repetitive with perhaps too much emphasis on the philosophy behind the design decisions, but most of the time these kinds of 15 minute video interviews with an executive aren't going to get into the technical weeds*. They're aren't really meant for people like us who have seen Johnny and other Apple executives interviewed before in video and print, but for the more casual Geekerwan viewer. I'm sure he has a large Chinese audience who don't necessarily consume lots of, especially English speaking, Apple content. Geekerwan covers more than just Apple so we shouldn't assume that everyone is as familiar with Apple's design ethos as we are.
*Which is not to say it was completely devoid of such content, as already noted Srouji's caveats about the A- and M-series GPU architectures being "almost identical" (beyond size) was interesting (would've liked a followup on that) - so were his oblique comments about vapor chambers being too large/thick for current iPhone designs. I would've also like to have seen more of a followup on Apple's performance data which Srouji mentioned several times as being key to their CPU design. Again, that would've been a longer video and I don't know how practiced an interviewer the Geekerwan host is.
*Which is not to say it was completely devoid of such content, as already noted Srouji's caveats about the A- and M-series GPU architectures being "almost identical" (beyond size) was interesting (would've liked a followup on that) - so were his oblique comments about vapor chambers being too large/thick for current iPhone designs. I would've also like to have seen more of a followup on Apple's performance data which Srouji mentioned several times as being key to their CPU design. Again, that would've been a longer video and I don't know how practiced an interviewer the Geekerwan host is.
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Didn't watch it, but did a word search through the transcript. Disappointed he didn't ask the obvious question about clock speeds: Why has Apple not allowed higher max clocks on the desktops than the laptops?* Is it an engineering limitation in the chips, or a business decision?
Also no question about why they've not yet transitioned to LPDDR6.
Then again, I suppose it's possible that Apple pre-approves all questions as a condition of the interview, and they didn't want to address those, and thus this may not be Geekerwan's fault.
*FWIW, here's how I would have phrased that question:
With Apple Silicon, you've done a brilliant job optimizing energy consumption vs. performance for mobile devices. But, as you know, desktops are different. Battery life is a non-issue, heat is much less of an issue, and there's an expection of higher performance with desktops.
Given this, why didn't you allow higher clockspeeds on your desktops than your laptops, at least on one or two cores? Is it because the higher clocks caused stability issues, or that you decided the power consumption increased too much relative to the performance gain, or was it a business decision rather than an enginnering one?
Also no question about why they've not yet transitioned to LPDDR6.
Then again, I suppose it's possible that Apple pre-approves all questions as a condition of the interview, and they didn't want to address those, and thus this may not be Geekerwan's fault.
*FWIW, here's how I would have phrased that question:
With Apple Silicon, you've done a brilliant job optimizing energy consumption vs. performance for mobile devices. But, as you know, desktops are different. Battery life is a non-issue, heat is much less of an issue, and there's an expection of higher performance with desktops.
Given this, why didn't you allow higher clockspeeds on your desktops than your laptops, at least on one or two cores? Is it because the higher clocks caused stability issues, or that you decided the power consumption increased too much relative to the performance gain, or was it a business decision rather than an enginnering one?
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In case anyone's interested, here's the transcript with the timestamps stripped using TimeWipe ( https://timewipe.deepakness.com/ ). Really impressed that MR's website allowed me to post all 3k+ words!
Johnny hi Johnny I'm R from J and nice to have you here today my pleasure good afternoon my pleasure to meet you so I heard you are kind of straightforward guide on Tech topics so maybe we can just step into the questions ASAP go ahead please so my first questions being obviously iPhone and the iPhone Pro Series are probably the first iPhones after you launch the Apple intelligence so how do aand apro chips contribute to running Apple intelligence and for wider pers perspective has Apple intelligence make any significant impact on your decision making when you're designing Apple silons and maybe overall Hardware yeah U so you're referring to Apple intelligence running on app silicon for the iPhone but we actually introduce and shipped our first neural engine implementation in and since then we've been improving our neural engine year-over-year and adding more performance with power efficiency and our colleagues from the software team has been leveraging and utilizing that engine then when you look at Apple intelligence running an apple silicon it utilizes the whole s so but it heavily also utilizes the neural engine which we also added support for Transformer models many years back and that's one of the reasons thatPro can support apple intelligence so with Aand Pro we took it even one step further we kept improving the neural engine even more than aPro we added more bandwidth to the system memory and we added more improvements across the whole so to to build a balanced compute memory subsystem including the capacity and the bandwidth on the computer so we built it from the ground up with apple intelligence in mind you actually upgraded to gig of RAM on iPhone Pro last year if I'm not mistaken the iPhone series are also you know having the upgrade for gigs of RAM which for me seems like a you know critical turning point so could you explain the necessity of you know bringing more Rams to iPhone is this decision solely driven by Apple intelligence or were other use cases such as gaming also considered so again our goal is to build the best products delivering the absolute best user experience as it relates to Apple intelligence dram is one aspect and when we look at what we're building whether it's silicon Hardware or software we don't want to be wasteful in many ways we have lots of data that tells us what is going to enable a certain feature and apple intelligence is one of those very very important features that we want to enable and we look at different configurations both for computation and memory bandwidth and memory capacity and then we made the right tradeoff and balance of what actually makes the most sense so Apple intelligence was a major feature that led us to believe that we we need to get to gab but having said that the gab is going to help immensely in many other applications including gaming a high highend gaming AAA title games and highend gaming on device so I think it's going to be really really beneficial the other thing to keep in mind uh this is one of the benefits of having the software and the silicon and the product fully integrated is that the software team our excellent software team will optimize not only for compute they'll also optimize for the memory footprint of each application so they don't end up also wasting memory so we look at all these trade-offs and we end up with here's what makes sense and GB was the most perfect choice for us I think would be a par question you know some of our competitors are having started to put more core counts into their CPU designs even the latest Apple Mchip has also increased the number of core counts compared to before and in contr the aseries continue to use let's say two performance cores and four efficiency cores it's a strategy that you have been used for quite some times why did the apple Mcons considered increasing the numbers of core counts while aPro didn't great question so maybe I will start with our philosophy and then I'll get to your to answer specifically your question our philosophy I I'll give you some uh some principles one of the principles is we want to build the same CPU architecture whether it's for a chip that goes into the phone or the iPad or the Mac or other configurations so it's a scalable architecture same applies to the graphics neural engine and others now one of the main benefits for that is for the software and developers you have a single architecture that you develop for the iPhone or the iPad or the Mac so that's big and by the way another side benefit is from a team efficiency you get to design one architecture so that's one principle some architecture across different chips the second principle is given we're not a merchant vendor we don't really need to Target a specific Peak Performance for a specific Corner case Benchmark that you may not even experience or hit as a customer just in order to win some Benchmark we care about again delivering the absolute best user experience and for that we look at lots of lots of data of how the devices the software is using the silicon and what makes the absolute best use and therefore we make that R based on that aspect a third principle which is important is you want to deliver the absolute best performance whether it's a CPU or Graphics but let's talk about CPU since that's your question with the highest performance at the best Absolute Energy Efficiency Energy Efficiency extremely extremely important for us so the best single thread and that's key because what others might be doing other vendors what they might be doing is they add multiple cores more and more cores in order to compensate for not so good single threat performance so one way to compensate is you add more cores uh and therefore you can achieve a certain Peak Performance at higher power larger die which means also larger cost so we don't do that either so now let me answer your question based on these principles when you look at the single thread of performance core across all of our silicon is the absolute best in the industry we're leading the industry if you look at the efficiency cores same we're at the absolute best we're like leading in a big way and then when we look at the configuration whether it's a selic that goes into the phone or the iPad or the mac and we have lots of simulation uh and performance modeling tools and we look at actual data and then we take into account for example the battery size for a product the power delivery system for a product the thermal envelope for the product because overbuilding again is wasteful for example for the phone we came to the conclusion that pe so two performance course for efficiency course meets the needs of what that device requires because we have the absolute best single thread and the efficiency cause is so good for other tasks and that configuration works then your next question was why did you make different choice for Mthat goes into the iPad those have larger thermal envelopes different Power delivery and therefore you can push the frequency and the performance to a different point so going to my first principle of using the same architecture across different chips we make the differentiation in implementation of frequency points operating points we enable Peak frequency in order to enable what we call best performance to give you the absolute best performance but we also look into Energy Efficiency and where the sustained needs to be and what is the shape of the curve when you look at Power performance so that your high performance maximum Energy Efficiency okay so the next question is about the microarchitecture you actually have a long period of time that micro architecture of a series CPUs was steadily updated before AI would say starting with APro you actually started to widen the your CPU of course uh we saw a wide decode on aPro and depends on the CPU upgrade we saw on Apple MI would say we expect a series CPU to widen further so my question is when you are making those decisions on CPU micro architectures you know how PPA trade-offs are made So my answer actually follows the same principle that just cover which is you want to design the best CPU for a certain silicon that goes into a certain product and we have lots of data and performance modeling to tell us what configuration makes the best use terms of highest power efficiency and performance obviously we're not going to get into micro architecture details on what plans we have in mind but you can imagine we have a deep line of CPU micro architecture not for this year next year for many years to come and we have modeling tools including what cash sizes you need for each of these course per implementation based on that we make those decisions and based on what's going to deliver the best user experience again not for a certain Benchmark now in my experience it proved to be the case that once you do that you actually end up winning lots of benchmarks and winning those while keeping your Energy Efficiency so it becomes a side benefit but again the strength that we have being an integrated part of Apple the full integration of the software the product team and the Silicon team where you design absolutely for what our product needs not for everyone else gives us the freedom to optimize what you call PPA power performance area for the absolute best Energy Efficiency and area it's science but it's science combined with art and you make the proper judgment codes based on tools and modeling of what actually going to deliver the best user experience so it's both okay so next question is about uh gaming on iPhones we saw developers bringing more and more AAA games to iPhone but obviously there are many inherent difference between mobile gpus and desktop or console gpus I say typically mobile memory subst system would be you know have much lower bandwidth mobile GPU rendering pipeline actually differs for example Apple's GPU are actually utilizing tile based defer rendering techniques instead of immediate rendering and also software development pipelines are quite you know distinct so I'm wondering what engineering challenges did you guys face when deciding to Port these triaa games to iPhone and how were they addressed and by the way again following one of the principle I just covered which is we want to build the same GPU architecture for all of our chips for example you can see that the GPU architecture fundamental that we built for the mac and for the iPhone are very similar the implementation are different and we can get to that later but the architecture is is similar and what that gives again to developers is they get to port or Implement a game for the iPhone and the mac and it's the same porting so that's great and the fact that our GPU is so performing that means that for example when you look at the phone including Pro is that it has longevity meaning you can looking forward for future games it will be able to support those at really high performance low power then when you look at different implementations whether it's a phone or a Mac this is where we make implementation differences and we're smart about how we do that during the implementation while keeping the architecture similar and it's not only frequency and operating points it's below that even meaning a lower level of details but in terms of the functional archit ecture is is the same of course you're working with different Power delivery and thermal envelopes which is why you can see that appid silicon shipping on a phone has different or less GPU cores than appid silicon shipping in a MacBook Pro but the fundamental what we call fstp the shaders Etc are very very similar and then we operate at different points again to maintain Energy Efficiency but the same grade Graphics you get all across we just talk about the running games on iPhone and also seral management is uh crucial factor for that this year you emphasized improvements on thermal management so can you specifically talk about what changes you've made for the Thal management the iPhone and the Pro Series and could you talk through decision making and also how does it differs from previous thermos systems again we build products and the idea is to deliver the best products and it's not only about theque performance for graphics at certain termal envelope and again this is where my team and the product team work hand in hand ahead of time about what is the absolute best decision we can make at the product level of course in terms of silicon you want more thermos you want bigger battery but that has to off on other aspects so we need to manage that piece and we highlight in the event this morning about some of the many thermal improvements that were were made into the iPhone series and that obviously benefits theid silicon that is enabling those iPhones but then you go back to the Energy Efficiency the fact that we have the most energy efficient chips it helps us and again when you don't chase Peak Performance at higher power and not so energy efficient versus sustained and best in performance you get to optimize for the overall system obviously we can get bit deeper into that you guys already implemented if I'm not wrong aluminum plate inside phone actually in the industry a lot of people are using let's say Vapor Chambers and other Solutions so when you are deciding new thermal solution what kind of as a mindset did you go through what kind of factors do you considers you know again the mindset is who want to deliver the best product not necessarily one thing the best product optimized for the absolute best user experience for example you can deliver a better thermal envelope if you have thicker devices you use different materials the example you gave is one more example but that's one tradeoff we believe if you take it to the extreme doesn't actually benefit the product because it has implications on the form factor and the ID so we take all consideration to account including the materials and how thick you can allow that product we want it thinner how much space you give battery and other components even the placement of components on the MLB make a difference so it's very thoughtful thorough process that takes into consideration many many aspects but the absolute number one priority is building for the absolute products not just thermal so that I can deliver a Peak Performance and saying I win this Benchmark we want to deliver the best absolute product and and the Energy Efficiency Focus we have all across enables all of this and again it's an optimization at the product level okay so the last question let's talk about video shooting on iPhone now so uh obviously iPhone have very great humaning capability compared to competitors what kind of roles did Apple silicons made in that kind of process well maybe for example Aseries inside iPhone and pros of course this started many many many years back uh we've been investing in our image silicon processor which is the ISP and same applies for other media engines so we've been investing in that space we believe we have the best absolute custom silicon that is built for these devices for example if you look at each frame that passes through our camera ISP it gets analyzed for things like color and tone when you look at the image signal processing as a pipeline it starts with a an excellent image information that gets into the high speed and then it gets defined even further by dedicated streaming machine learning based processing that have been trained on millions of photos before that and those run on the new engine so you can see the tight integration between the new engine and the IP in this case now the new engine also provides detailed semantic information about the overall scene including the subjects various subjects and the intent of the photographers now what this does it enables the camera to deliver a wider range of dynamic information based on the scene and the materials in the scene Etc and we get to do that very very fast at a high rate k frames per second so that's great then post ISP as as that gets processed we have another media engine called the video encoder that compresses the video at billion pixels per second so when you combine both you get to a very high rate that's how we enable Dolby Vision K frames per second sometimes you can see that others you know our competitors can generate through lots of software processing a good frame a good picture at one time but we're first in terms of delivering a video for D Vision Video K capture um and that's thanks to the tight integration of the Silicon different IPS on the software and the camera control it's like the physics camera control and the Silicon including the ISP they all work together I think that's all the question we have today so thank you my pleasure thank you thank you thank
Johnny hi Johnny I'm R from J and nice to have you here today my pleasure good afternoon my pleasure to meet you so I heard you are kind of straightforward guide on Tech topics so maybe we can just step into the questions ASAP go ahead please so my first questions being obviously iPhone and the iPhone Pro Series are probably the first iPhones after you launch the Apple intelligence so how do aand apro chips contribute to running Apple intelligence and for wider pers perspective has Apple intelligence make any significant impact on your decision making when you're designing Apple silons and maybe overall Hardware yeah U so you're referring to Apple intelligence running on app silicon for the iPhone but we actually introduce and shipped our first neural engine implementation in and since then we've been improving our neural engine year-over-year and adding more performance with power efficiency and our colleagues from the software team has been leveraging and utilizing that engine then when you look at Apple intelligence running an apple silicon it utilizes the whole s so but it heavily also utilizes the neural engine which we also added support for Transformer models many years back and that's one of the reasons thatPro can support apple intelligence so with Aand Pro we took it even one step further we kept improving the neural engine even more than aPro we added more bandwidth to the system memory and we added more improvements across the whole so to to build a balanced compute memory subsystem including the capacity and the bandwidth on the computer so we built it from the ground up with apple intelligence in mind you actually upgraded to gig of RAM on iPhone Pro last year if I'm not mistaken the iPhone series are also you know having the upgrade for gigs of RAM which for me seems like a you know critical turning point so could you explain the necessity of you know bringing more Rams to iPhone is this decision solely driven by Apple intelligence or were other use cases such as gaming also considered so again our goal is to build the best products delivering the absolute best user experience as it relates to Apple intelligence dram is one aspect and when we look at what we're building whether it's silicon Hardware or software we don't want to be wasteful in many ways we have lots of data that tells us what is going to enable a certain feature and apple intelligence is one of those very very important features that we want to enable and we look at different configurations both for computation and memory bandwidth and memory capacity and then we made the right tradeoff and balance of what actually makes the most sense so Apple intelligence was a major feature that led us to believe that we we need to get to gab but having said that the gab is going to help immensely in many other applications including gaming a high highend gaming AAA title games and highend gaming on device so I think it's going to be really really beneficial the other thing to keep in mind uh this is one of the benefits of having the software and the silicon and the product fully integrated is that the software team our excellent software team will optimize not only for compute they'll also optimize for the memory footprint of each application so they don't end up also wasting memory so we look at all these trade-offs and we end up with here's what makes sense and GB was the most perfect choice for us I think would be a par question you know some of our competitors are having started to put more core counts into their CPU designs even the latest Apple Mchip has also increased the number of core counts compared to before and in contr the aseries continue to use let's say two performance cores and four efficiency cores it's a strategy that you have been used for quite some times why did the apple Mcons considered increasing the numbers of core counts while aPro didn't great question so maybe I will start with our philosophy and then I'll get to your to answer specifically your question our philosophy I I'll give you some uh some principles one of the principles is we want to build the same CPU architecture whether it's for a chip that goes into the phone or the iPad or the Mac or other configurations so it's a scalable architecture same applies to the graphics neural engine and others now one of the main benefits for that is for the software and developers you have a single architecture that you develop for the iPhone or the iPad or the Mac so that's big and by the way another side benefit is from a team efficiency you get to design one architecture so that's one principle some architecture across different chips the second principle is given we're not a merchant vendor we don't really need to Target a specific Peak Performance for a specific Corner case Benchmark that you may not even experience or hit as a customer just in order to win some Benchmark we care about again delivering the absolute best user experience and for that we look at lots of lots of data of how the devices the software is using the silicon and what makes the absolute best use and therefore we make that R based on that aspect a third principle which is important is you want to deliver the absolute best performance whether it's a CPU or Graphics but let's talk about CPU since that's your question with the highest performance at the best Absolute Energy Efficiency Energy Efficiency extremely extremely important for us so the best single thread and that's key because what others might be doing other vendors what they might be doing is they add multiple cores more and more cores in order to compensate for not so good single threat performance so one way to compensate is you add more cores uh and therefore you can achieve a certain Peak Performance at higher power larger die which means also larger cost so we don't do that either so now let me answer your question based on these principles when you look at the single thread of performance core across all of our silicon is the absolute best in the industry we're leading the industry if you look at the efficiency cores same we're at the absolute best we're like leading in a big way and then when we look at the configuration whether it's a selic that goes into the phone or the iPad or the mac and we have lots of simulation uh and performance modeling tools and we look at actual data and then we take into account for example the battery size for a product the power delivery system for a product the thermal envelope for the product because overbuilding again is wasteful for example for the phone we came to the conclusion that pe so two performance course for efficiency course meets the needs of what that device requires because we have the absolute best single thread and the efficiency cause is so good for other tasks and that configuration works then your next question was why did you make different choice for Mthat goes into the iPad those have larger thermal envelopes different Power delivery and therefore you can push the frequency and the performance to a different point so going to my first principle of using the same architecture across different chips we make the differentiation in implementation of frequency points operating points we enable Peak frequency in order to enable what we call best performance to give you the absolute best performance but we also look into Energy Efficiency and where the sustained needs to be and what is the shape of the curve when you look at Power performance so that your high performance maximum Energy Efficiency okay so the next question is about the microarchitecture you actually have a long period of time that micro architecture of a series CPUs was steadily updated before AI would say starting with APro you actually started to widen the your CPU of course uh we saw a wide decode on aPro and depends on the CPU upgrade we saw on Apple MI would say we expect a series CPU to widen further so my question is when you are making those decisions on CPU micro architectures you know how PPA trade-offs are made So my answer actually follows the same principle that just cover which is you want to design the best CPU for a certain silicon that goes into a certain product and we have lots of data and performance modeling to tell us what configuration makes the best use terms of highest power efficiency and performance obviously we're not going to get into micro architecture details on what plans we have in mind but you can imagine we have a deep line of CPU micro architecture not for this year next year for many years to come and we have modeling tools including what cash sizes you need for each of these course per implementation based on that we make those decisions and based on what's going to deliver the best user experience again not for a certain Benchmark now in my experience it proved to be the case that once you do that you actually end up winning lots of benchmarks and winning those while keeping your Energy Efficiency so it becomes a side benefit but again the strength that we have being an integrated part of Apple the full integration of the software the product team and the Silicon team where you design absolutely for what our product needs not for everyone else gives us the freedom to optimize what you call PPA power performance area for the absolute best Energy Efficiency and area it's science but it's science combined with art and you make the proper judgment codes based on tools and modeling of what actually going to deliver the best user experience so it's both okay so next question is about uh gaming on iPhones we saw developers bringing more and more AAA games to iPhone but obviously there are many inherent difference between mobile gpus and desktop or console gpus I say typically mobile memory subst system would be you know have much lower bandwidth mobile GPU rendering pipeline actually differs for example Apple's GPU are actually utilizing tile based defer rendering techniques instead of immediate rendering and also software development pipelines are quite you know distinct so I'm wondering what engineering challenges did you guys face when deciding to Port these triaa games to iPhone and how were they addressed and by the way again following one of the principle I just covered which is we want to build the same GPU architecture for all of our chips for example you can see that the GPU architecture fundamental that we built for the mac and for the iPhone are very similar the implementation are different and we can get to that later but the architecture is is similar and what that gives again to developers is they get to port or Implement a game for the iPhone and the mac and it's the same porting so that's great and the fact that our GPU is so performing that means that for example when you look at the phone including Pro is that it has longevity meaning you can looking forward for future games it will be able to support those at really high performance low power then when you look at different implementations whether it's a phone or a Mac this is where we make implementation differences and we're smart about how we do that during the implementation while keeping the architecture similar and it's not only frequency and operating points it's below that even meaning a lower level of details but in terms of the functional archit ecture is is the same of course you're working with different Power delivery and thermal envelopes which is why you can see that appid silicon shipping on a phone has different or less GPU cores than appid silicon shipping in a MacBook Pro but the fundamental what we call fstp the shaders Etc are very very similar and then we operate at different points again to maintain Energy Efficiency but the same grade Graphics you get all across we just talk about the running games on iPhone and also seral management is uh crucial factor for that this year you emphasized improvements on thermal management so can you specifically talk about what changes you've made for the Thal management the iPhone and the Pro Series and could you talk through decision making and also how does it differs from previous thermos systems again we build products and the idea is to deliver the best products and it's not only about theque performance for graphics at certain termal envelope and again this is where my team and the product team work hand in hand ahead of time about what is the absolute best decision we can make at the product level of course in terms of silicon you want more thermos you want bigger battery but that has to off on other aspects so we need to manage that piece and we highlight in the event this morning about some of the many thermal improvements that were were made into the iPhone series and that obviously benefits theid silicon that is enabling those iPhones but then you go back to the Energy Efficiency the fact that we have the most energy efficient chips it helps us and again when you don't chase Peak Performance at higher power and not so energy efficient versus sustained and best in performance you get to optimize for the overall system obviously we can get bit deeper into that you guys already implemented if I'm not wrong aluminum plate inside phone actually in the industry a lot of people are using let's say Vapor Chambers and other Solutions so when you are deciding new thermal solution what kind of as a mindset did you go through what kind of factors do you considers you know again the mindset is who want to deliver the best product not necessarily one thing the best product optimized for the absolute best user experience for example you can deliver a better thermal envelope if you have thicker devices you use different materials the example you gave is one more example but that's one tradeoff we believe if you take it to the extreme doesn't actually benefit the product because it has implications on the form factor and the ID so we take all consideration to account including the materials and how thick you can allow that product we want it thinner how much space you give battery and other components even the placement of components on the MLB make a difference so it's very thoughtful thorough process that takes into consideration many many aspects but the absolute number one priority is building for the absolute products not just thermal so that I can deliver a Peak Performance and saying I win this Benchmark we want to deliver the best absolute product and and the Energy Efficiency Focus we have all across enables all of this and again it's an optimization at the product level okay so the last question let's talk about video shooting on iPhone now so uh obviously iPhone have very great humaning capability compared to competitors what kind of roles did Apple silicons made in that kind of process well maybe for example Aseries inside iPhone and pros of course this started many many many years back uh we've been investing in our image silicon processor which is the ISP and same applies for other media engines so we've been investing in that space we believe we have the best absolute custom silicon that is built for these devices for example if you look at each frame that passes through our camera ISP it gets analyzed for things like color and tone when you look at the image signal processing as a pipeline it starts with a an excellent image information that gets into the high speed and then it gets defined even further by dedicated streaming machine learning based processing that have been trained on millions of photos before that and those run on the new engine so you can see the tight integration between the new engine and the IP in this case now the new engine also provides detailed semantic information about the overall scene including the subjects various subjects and the intent of the photographers now what this does it enables the camera to deliver a wider range of dynamic information based on the scene and the materials in the scene Etc and we get to do that very very fast at a high rate k frames per second so that's great then post ISP as as that gets processed we have another media engine called the video encoder that compresses the video at billion pixels per second so when you combine both you get to a very high rate that's how we enable Dolby Vision K frames per second sometimes you can see that others you know our competitors can generate through lots of software processing a good frame a good picture at one time but we're first in terms of delivering a video for D Vision Video K capture um and that's thanks to the tight integration of the Silicon different IPS on the software and the camera control it's like the physics camera control and the Silicon including the ISP they all work together I think that's all the question we have today so thank you my pleasure thank you thank you thank
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Geekerwan is very big in China, which is why they are getting attention. Their reviews however are rather shallow and the empirical data they produce are of low quality.
On the other hand, Chips and Cheese are an excellent team who really try to understand and explain the architecture.
Chips and Cheese had little interest in Apple products so far and they are also not nearly as big as Geekerwan.
I’ll answer it based on how he answered every question:
“We want to build the best products with the best experience. If you look at our desktop products, they offer outstanding performance single core and multi core performance while making little to no fan noise. That’s what we try to do across the entire Mac lineup.”
In reality, the reasons most likely center around having a fairly consistent performance level across all Macs that have the same chip. Another reason could just be that desktop market share is so low that they don’t bother pushing the wattage higher. It takes more testing, validation, components that are designed for higher power, etc. Lastly, I think when they introduce power curve charts for new chips, they want the numbers to apply to the desktops as well for consistent messaging. It’s not that easy for Apple to say the Max is 5x more efficient than competitors but on the desktop, it’s only 2x.
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True, but that sort of misses my point, which I was attempting to make humorously with my comment, namely that Apple execs avoid doing technical interviews (unless I've missed them).
For instance, AnandTech was big—big enough to land interviews with Lisa Su (AMD CEO), Mike Clark (AMD Zen Chief Architect), and Ann Kelleher (EVP and GM of Foundry Technology Development at Intel). And while not their primary focus, AnandTech did have an interest in Apple products.
Yet I couldn't find a single instance in which AnandTech landed an interview with Apple execs. So my humorous point remains: Perhaps I've missed it, but I've not seen Apple execs do interviews with anyone they know is going to ask them serious technical questions.
Those all sound plausible—they're all reasonable speculations—but I don't think any of them actually apply:
1) Desire for consistent performance: Apple gave a higher max clock speed to the 16" M2 Max MPB than the 14" M2 Max MPB. So if they don't mind having different performance within the same product line, clearly they wouldn't be concered about a qualitatively different type of product line (a desktop) performing differently. Indeed, product differentiation is a valuable thing.
2) Messaging about efficiency: If you look at Apple's marketing for the Mac Pro and Mac Studio on Apple.com, you'll see it's all about performance. That's where they're doing the quantitative comparisons. When it comes to power efficiency, there's just a single fluffy mention in the ad copies of each product (Studio: "Thanks to the efficiency of Apple silicon...."; MP: "And thanks to the power efficiency of Apple silicon, the new Mac Pro runs even cooler and quieter under heavy workloads — truly a workstation you can work next to.").
3) Chip validation: The Ultra requires separate validation from the laptop chips, so they could certainly test higher clockspeeds as part of that. Plus there were rumors from credible sources that Apple was testing the chips for the desktops at higher clockspeeds.
My own speculation is that Apple optimized their AS CPU cores principally for mobile (iPhone/laptop) operation, since those are much bigger markets than the desktops, and that they thus aren't well-designed to handle the higher voltages that significantly higher clock speeds would require. Apple wants the performance bragging rights, and if the chips could handle the higher clocks in their larger desktops, I suspect they would have offered them with those.
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I think you're being a little unfair to them. Can anyone other than Cheese and Chips provide better reviews and empirical data?
They may have a financial problem with Apple hardware. Since testing PC components is cheaper than testing Apple hardware, I can imagine why they started with that first. Now that they are more popular, some PC companies lend them hardware to test, so I can understand why they keep testing PC components.
I fully agree with you - Apple execs won’t talk about technical details, certainly not when it comes to products roadmaps. They are also unlikely to talk about implementation details (like RAM or cooling). I think one can still ask certain technical questions, like their choice of integrating the programmable matrix coprocessor with the CPU rather than the GPU and what it entails for programmability and performance; or the split between the integer and vector execution backends and what it means for SIMD usability. I think a question about desktop performance is also a fair one, if one finds a good way to formulate it.
Geekerwan has tremendous amount of money and resources. They could provide high quality data. They just choose not to. Their methodology is vague and the results are all over the place.
Testing Apple stuff can be difficult because you often don’t have access to the APIs and tools that facilitate low-level diagnostics. For example, you can’t pin work to specific cores which limits certain types of tests you can do. But otherwise, testing Apple hardware is super cheap because of the no questions asked return period. You can buy the device, run your tests, and return it.
What makes you think that? Do you think they have more money and resources than other popular YouTube tech channels like GamerNexus?
If their results are popular, it's because no one else does what they do. Even if they don't have early access to Apple hardware, their reviews become popular even if it's the umpteenth review of the same hardware.
Geekerwan may not be as good as Anandtech used to be, but the truth is that apart from Chips and Cheese, no one else is doing what they are doing.
Both things can be true. I agree very few (maybe none) do what they do. It’s also true to say their methodology is vague and results are all over the place.
It’s just the sad state of reviews.
Then I need to know what you mean by “giving desktop more power”. How much more power? 10w more? 100w more? If it’s the former, my point is invalid. If it’s the latter, my point stands.
Same point as above. If Apple touts the Max as 5x more consistent, but only in a MacBook Pro and not a Studio, then it confuses people. Apple is all about simplicity in marketing.
When you put something in quotes in responding to me, that indicates to other readers that I used that phrase, which I did not. Besides, if I did, I would have said I wanted "moar powah" 😆
I'm not sure how much power would be required to increase the max clock on two M4 performance cores from, say 4.4 GHz to 5.0 GHz, but I am sure it's much closer to 10W than 100 W. If it's an additional 10 W/core, that would be 20 W.
I think you're focusing too much on that. Note that there are many differences between the laptop and desktop product lines, and Apple has no problems marking both. If Apple were to restrict desktop performance purely to attain marketing consistency with one of its laptop product lines, I think they would be seeking what Emerson termed "a foolish consistency". And I don't think Apple would be foolish in that way.
And you're right, they focus on simplicity in marketing. Their ads are much more high-concept. Which means they typically don't even give numerical comparisons. Look at this ad for the first-gen Studio starting at 1:44 here. Not a single numerical comparison! So it's a non-issue.
Yeah, they mention them at WWDC, but I'm sure they can think of some clever way to address that. And the audience that views WWDC doesn't really seek or need simplicity.
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I agree with @theorist9. Srouji is not telling the whole story. I believe the statement about Apple Silicon design not being driven by winning benchmarks - but at the same time I am certain that they do pay attention to benchmarks. The higher clock on the M2 Max is a testament to that. It is likely that Apple did not achieve the performance goals with the base M2 clock compared to the competition, and raised the clocks on the high-end models in order to improve the psychological value proposition.
I believe that this tells us multiple things. For example, Apple does pay attention to other products and balances their performance targets accordingly. At the same time, it also tells us that Apple designs likely have some headroom at the top end. This puts Apples strategy at a contrast to that of other manufacturers, who aggressively use binning to provide a premium product at a higher performance point. Apple is willing to take a small performance hit for the sake of consistent performance.
I believe that this tells us multiple things. For example, Apple does pay attention to other products and balances their performance targets accordingly. At the same time, it also tells us that Apple designs likely have some headroom at the top end. This puts Apples strategy at a contrast to that of other manufacturers, who aggressively use binning to provide a premium product at a higher performance point. Apple is willing to take a small performance hit for the sake of consistent performance.
Why boost only two P cores? M4 is already head and shoulders above the competition in ST speed. Boosting two cores won't yield much difference in benchmark bragging rights.
Just FYI, Intel's PL2 Alder Lake boost uses ~120w more and only provides 10-20% more performance.
I'm sure Apple has a bit more headroom since they're already so low in starting wattage, but I think to get any meaningful benchmark bragging rights, it'll be much closer to 100w than 10w.