111–120 of 148 posts
Media is so focused on CPUs, they are missing the fact that Apple focused on the GPU and Neural Engine for this round of chips
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I have two monitors connected to M1 mac. One works perfectly fine and is automatically RGB. Other flickers and when changing to RGB mode it is lime green. Wonder why it is not problem with Intel Macs and if M3 fixes those bugs? Maybe it is Apples feature to sell more of their own monitors. They make sure other high end brands do not work with macOS. It does not make sense that this kind of bug is 3 years active.
> Wonder why it is not problem with Intel Macs and if M3 fixes those bugs? Let’s guess: maybe they have different drivers? Would be far from surprising, given that they’re running on different processors.
They advised me to buy Apple Display.
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While FP32 non tensor flops at least looks comparable, FP16/BF16 with tensor core(nowadays a default for any neural network including LLM) at 330 TFlops/s blows away M2.
Many of us still use our graphics chips for graphics, where FP32 is king.
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I guess parent forgot "on macOS and iOS". Technically every game on macOS or iOS is running on Metal, because the Apple OpenGL implementations are also running on top of Metal for quite a while now ;) Across platforms, there's no chance in hell that more games run on Metal than DirectX, not even when counting iOS shovelware.
Metal owns a significantly bigger market for gaming revenue than DirectX.
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Well, they got into that position starting from a near bankrupt company, which couldn't negotiate anything exclusive, and which was for a long time at the mercy of Motorola and the Intel. So it's something they took advantage of after they grew (well, which company at their scale wouldn't ask for the best wholesale deals?), but not what made them big in the first place.
What made them big in the first place were the iPod/iTunes/iPhone and the ludicrous revenues from the App Store. The iPod's only notable hardware that wasn't just a random off the shelf part was the click wheel, the chips were all off-the-shelf (until old iPhone chips counted as that), and iPhones didn't get custom chips until the 4. So I guess the other part of the winning formula is "use market dominance in one sec…
The iPod/iPhone yes, but "in the first place" the App Store was insignificant (the remenues at 2010 was For comparison the iPod had that profit already in 2004, and around 3 billion in 2010 (when the iPhone had already started replacing it).
So, the App Store was hardly ludicrous revenue for its first 3-4 years, in fact less than 10% of Apple's revenue. The iTunes store even less so.
It's the iPod and then iPhone that made Apple's dominance. The big store profit came later (and the iTunes/Music profit never was that big).
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Well, they got into that position starting from a near bankrupt company, which couldn't negotiate anything exclusive, and which was for a long time at the mercy of Motorola and the Intel. So it's something they took advantage of after they grew (well, which company at their scale wouldn't ask for the best wholesale deals?), but not what made them big in the first place.
What made them big in the first place were the iPod/iTunes/iPhone and the ludicrous revenues from the App Store. The iPod's only notable hardware that wasn't just a random off the shelf part was the click wheel, the chips were all off-the-shelf (until old iPhone chips counted as that), and iPhones didn't get custom chips until the 4. So I guess the other part of the winning formula is "use market dominance in one sec…
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So, in NVIDIA parlance, my Skylake laptop would have 128 "cuda cores"? 128 = 4 (physical cores) * 2 (hyperthreading) * 8 (AVX2 f32 lanes) * 2 (floating point ports per core)
Sorta, yeah! Also, your "128 cuda cores" of Skylake variety run at higher frequencies and work off of much bigger caches, so they are faster (in serial manner)... ...until they are slower, because GPU's latency hiding mechanism (with occupancy) hides load latencies very well, while CPU just stalls the pipeline on every cache miss for ungodly amounts of time... ...until they are faster again when the shader program us…
> ...until they are slower, because GPU's latency hiding mechanism (with occupancy) hides load latencies very well, while CPU just stalls the pipeline on every cache miss for ungodly amounts of time...
Is the GPU latency hiding mechanism equivalent to SMT/Hyperthreading, but with more threads per physical core? Or is there more machinery?
Also, how akin GPUs "stream multiprocessors"/cores are to CPUs ones at the microarchitectural level? Are they out-of-order? Do they do register renaming?
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> they don't have billions in pocket change they don't know how to spend otherwise your parent comment's example is literally Google, world-class experts at burning money on developers producing a million dead-end products and abandoning them a year later. if Google would get some sensible leadership, focus on a few core products, and stick with them for a decade, they'd have just as much money to spend. But "focus"…
> My point: the 'winning formula' of Apple is laser-sharp focus: have a few products, do them as well as anyone else or better, and only introduce a new product if it is mature-ish and very profitable. (We'll see how the vision headset fits in here) They also aimed at markets that are ripe for disruption, because of weak competition: The MP3 player market before the iPod, the PDA-with-a-SIM-card market before the iPh…
What heavily competitive market, the mobile phone duopoly?
Google has half the market, they are not the poor incumbent that doesn't have enough money to be disruptive.
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"128 * the-number-of-cores" of threads can make progress truly in parallel (at the same time). 24,576 threads (or however many, I didn't validate the number and it depends on the occupancy, which depends on thread resource usage, like registers => depends on the shader program code) is how many threads can be executed concurrently (as opposed to in parallel), as in, how many of them can simultaneously reside on the G…
So, in NVIDIA parlance, my Skylake laptop would have 128 "cuda cores"? 128 = 4 (physical cores) * 2 (hyperthreading) * 8 (AVX2 f32 lanes) * 2 (floating point ports per core)