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):
>"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."
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."