
Ask HN: State of GC on GPU? - cztomsik
I&#x27;ve googled something already but is this really dead? Memory should not be a problem anymore with on-chip GPU (shared RAM).<p>Few interesting links:
https:&#x2F;&#x2F;people.eecs.berkeley.edu&#x2F;~maas&#x2F;papers&#x2F;maas-ismm12-gpugc.pdf
http:&#x2F;&#x2F;lambda-the-ultimate.org&#x2F;node&#x2F;5006
http:&#x2F;&#x2F;mail.openjdk.java.net&#x2F;pipermail&#x2F;sumatra-dev&#x2F;2013-July&#x2F;000156.html
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yoklov
I’d be surprised if it were fruitful. GPUs are basically a few dozen
relatively slow cores, with very wide SIMD widths (and also some amount of
fixed fn hardware, but that’s not super important here). This isn’t at all
what you want for any GC algorithms that I know of.

That’s ignoring the overhead for copying data between CPU and GPU which I’m
unsure you can completely remove even if they share memory.

