alt Hacker Newsfor context:
"""
Description
The main goal of ggml is to be a simple, portable, and efficient tensor library for machine learning with minimal setup.
Plain C/C++ implementation without any dependencies
Cross-platform - x86, ARM, RISC-V, LoongArch, PowerPC, s390x, and WebAssembly
SIMD-optimized kernels for x86, ARM, and RISC-V
Broad backend support - CPU, GPU, NPU, and browser
2- to 8-bit integer quantization, plus MXFP4 and NVFP4 microscaling formats
Zero memory allocations during runtime
"""
As a mainframer, love to see the s390x support and zdnn (C library with all the instructions for our on chip accelerators) support. I like that IBM and Broadcom et al. went with something open source and local that could be tested on our Linux machines so that it wouldn't be a big pain to implement on z/OS or zLinux so to speak.
I've had the opportunity to do some fun playing around with zdnn on a z17. I've not tried the Spyre cards, but the on chip accelerator for Telum II is surprisingly capable with smaller models. I initially thought you would basically NEED the Spyre cards to get anything significant running but I was wrong.