Comments (5)
meton-robean
commented on June 2, 2024
循环分类与建模
将循环分成几大类，包含可以全并行的，含有寄存器依赖的，内存依赖的，动态边界的。根据这个新增两种指令:
所以一个创新点是根据循环的分类，自定义两种指令，其实本质是: 不是简单的新加指令，而是从指令的角度去看待，给指令增加一点新的语义信息，可以看做是一种语义标签，来使得后面的加速硬件可以识别循环内那几条特殊标记的指令，从而调度循环加速。
from papernotes.
meton-robean
commented on June 2, 2024
加速架构
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发掘迭代间的并行. 每个Lane负责某次循环迭代的执行，也就是每个lane需要执行某次迭代内的循环内的指令，类似多核的感觉，实际上每个Lane里面也确实就只有一个核通用CPU一样的ALU。
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但是其实这种多核加速的加速比大致取决于核的数目，并不高。 好处是每个lane负责一次迭代，就算循环内有分支啥的条件语句啥的也可以想像普通CPU一样执行.
from papernotes.
meton-robean
commented on June 2, 2024
XLOOP是利用 PyMTL和Pydgin来进行硬件实现和模型仿真
from papernotes.
meton-robean
commented on June 2, 2024
无依赖可全并行的执行例子
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meton-robean
commented on June 2, 2024
有内存依赖的执行例子
例如 A[ i] = A[i] +A[i-k]
有内存依赖的情况， 某个Lane如果check到在其负责的迭代里面，它需要的那个数在其他lane没有算好送到它这里，那么要终止本次迭代的执行，下一次再重新执行这一次迭代的指令们
from papernotes.
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