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  roadbuster
  "Processor-in-Memory", is an age-old idea which was even explored in a doctoral thesis from 1998: "Computational RAM: A Memory-SIMD Hybrid"*. At the time, the motivation was, "Between a DRAM chip and a microprocessor mounted on a circuit board, we can only get a few hundred megabytes per second of bandwidth. However, inside the memory chip itself, there's hundreds of gigabytes (terabits) of bandwidth available, so why not move some of the logic there?". And then the author pushed it to the extreme where there was a wide array of 1-bit processors at each column of DRAM. (Note: the reason why true PIM isn't viable is because of the radically different semiconductor process used for DRAM vs. high-speed digital logic, i.e.: your digital logic circuits will perform poorly on a "DRAM process").The designers of HBM5 had the same observations and thought, "why don't we put a logic chip at the bottom of the stack of HBM DRAM chips and get extremely high memory bandwidth?" But, in looking at this, you'll also quickly realize this is almost exactly what Intel and Micron pitched 15 years ago as Hybrid Memory Cube** (which lost on the market compared to the simpler, less costly, and more flexible alternative, HBM)* https://www.eecg.toronto.edu/~stumm/Theses/Elliott-PhD98.pdf** https://en.wikipedia.org/wiki/Hybrid_Memory_Cube
• honr
  Compute In Memory has been most of what electronics research (more accurately, the parts I am interacting with) talking about this year. There are a few trends and I am curious to see which ones survive in the market. RAM designers are hot in the market and job openings at the moment.
• MBCook
  So they built a very specific operation into the RAM. This RAM would only be useful for AI, otherwise the transistors are just wasted.And if we fund a different set of operations actually work better for AI you can’t adjust to that either.Seems extremely limited. But otherwise wouldn’t you just end up with something like a massive number of tiny microcontrollers each accessing a set of memory? The Transputer again.
• jcranmer
  Processing in memory was one of the extra topics we covered in my grad computer architecture class. Fifteen years ago. And even then, it was very clearly an old-hat idea.One of the problems with trying to move a lot of ALUs close to the DRAM logic is that ALUs are pretty hot, and DRAM is some of the most sensitive components to heat. There are some other issues too, like the process manufacturing differences mentioned by a sibling comment.
• senshan
  Why does not the article say anything on how KV-cache is handled with in-DRAM processing? Is this trivially obvious?
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  StilesCrisis
  "DRAM banks already provide most of the bandwidth; the external pins cannot expose it." Closed the tab.
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  peter_d_sherman
  I like the idea of a CPU/GPU/TPU on RAM (look at those gorgeous bandwidth numbers!) -- but I also wonder what problems it may potentially bring in the future... I think it would be a good idea that if RAM is to implement processors / PIM on it in the future, that each RAM stick should have an external DIP "safety" switch on the side which switches off such processing. If this switch is flipped by the user, then the stick simply falls back to operating as normal "dumb" RAM, driven by external CPU control. Also, it would be a good idea to have debug ports, debug proxying, single step capability, etc., in these futuristic RAM sticks, as well...Related:"SIMDRAM: A Framework for Bit-Serial SIMD Processing Using DRAM Extended Abstract" (2020):https://arxiv.org/html/2012.11890v1>"We leverage the SIMDRAM framework to accelerate seven application kernels from machine learning, databases, and image processing (VGG-13 [63], VGG-16 [63], LeNET [38], kNN [42], TPC-H [66], BitWeaving [45], Brightness [28]). SIMDRAM provides up to 2.5× speedup for the kernels compared to Ambit [58]. Compared to a CPU and a high-end GPU, SIMDRAM is 257× and 31× more energy efficient, while providing 93 × and 6× higher throughput, respectively."
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  RetroTechie
  AI focussed - as so much these days. Some corp. please put general-purpose cores in that RAM?
• moron4hire
  What ever happened to the idea of using memristors for this?
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  api
  Integrated RAM with tensor processing seems like the end game for silicon that's actually efficient at running AI models.Or integrated flash with TPUs? That would be awesome. Flash your model onto a model-processor and run it.
• tug2024
  [dead]
• paretolaw
  So, long samsung and short nvidia