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0 pointsdeepnotderp8y ago0 comments

Relying upon a JIT often means the ability to create things which preclude the use of static compilers, which means that accelerated hardware, like ours, cannot be used efficiently.

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yorwba8y ago

The kind of optimizations a static compiler might apply can be done by a JIT as well, with the added benefit of actually knowing what kind of workload is going to run. Most of deep learning is applying comparatively small computation graphs to very large arrays of numbers in parallel, so the overhead of compilation is only a small portion of the overall computation time. A smart JIT that decides on the optimal tiling pattern for the array dimensions observed at runtime and rewrites loops accordingly can easily pay for itself.

Firadeoclus8y ago

As a counterpoint (and not necessarily the one the GP is referring to), if you were compiling for, say, an FPGA the overhead of compilation would be very significant.

deepnotderpOP8y ago

Our processor is analogous to a CGRA, so compilation to it would indeed be hindered by a JIT based compiler.

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