| Fala Taelin, nice work! Does HVM2 compile interaction nets to e.g. spirv, or is this an interpreter (like the original HVM) that happens to run on the GPU? I ask because a while back I was messing around with compiling interaction nets to C after reducing as much of the program as possible (without reducing the inputs), as a form of whole program optimization. Wouldn't be too much harder to target a shader language. Edit: Oh I see... > This repository provides a low-level IR language for specifying the HVM2 nets, and a compiler from that language to C and CUDA
HVM Will have to look at the code then! https://github.com/HigherOrderCO/HVM Edit: Wait nvm, it looks like the HVM2 cuda runtime is an interpreter, that traverses an in-memory graph and applies reductions. https://github.com/HigherOrderCO/HVM/blob/5de3e7ed8f1fcee6f2... I was talking about traversing an interaction net to recover a lambda-calculus-like term, which can be lowered to C a la lisp in small pieces with minimal runtime overhead. Honestly the motivation is, you are unlikely to outperform a hand-written GPU kernel for like ML workloads using Bend. In theory, HVM could act as glue, stitching together and parallelizing the dispatch order of compute kernels, but you need a good FFI to do that. Interaction nets are hard to translate across FFI boundaries. But, if you compile nets to C, keeping track of FFI compute kernel nodes embedded in the interaction network, you can recover a sensible FFI with no translation overhead. The other option is implementing HVM in hardware, which I've been messing around with on a spare FPGA. |