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We haven't tracked posts mentioning Fable yet.
Tracking mentions began in Dec 2020.
A list of compiler projects and papers for tensor computation and deep learning
1 project | news.ycombinator.com | 7 Feb 2021
A List of Tensor Compilers
1 project | news.ycombinator.com | 4 Feb 2021
C-for-Metal: High Performance SIMD Programming on Intel GPUs
2 projects | news.ycombinator.com | 29 Jan 2021
Compiling from high-level lang to GPU is a huge problem, and we greatly appreciate efforts to solve it.
If I understand correctly, this (CM) allows for C-style fine-level control over a GPU device as though it were a CPU.
However, it does not appear to address data transit (critical for performance). Compilation and operator fusing to minimize transit is possibly more important. See Graphcore Poplar, Tensorflow XLA, Arrayfire, Pytorch Glow, etc.
Further, this obviously only applies to Intel GPUs, so investing time in utilizing low-level control is possibly a hardware dead-end.
Dream world for programmers is one where data transit and hardware architecture are taken into account without living inside a proprietary DSL Conversely, it is obviously against hardware manufacturers' interests to create this.
Is MLIR / LLVM going to solve this? This list has been interesting to consider:
What are some alternatives?
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