yuya-isaka/HPU
Accelerator for Hyperdimensional Computing (HDC)
This is a specialized hardware accelerator designed to dramatically speed up Hyperdimensional Computing (HDC) tasks. It takes raw data and processes it into high-dimensional vectors, outputting faster results for cognitive tasks like image or speech recognition while consuming less power. It's intended for engineers or researchers working on embedded systems or specialized hardware for AI applications.
No commits in the last 6 months.
Use this if you are developing or implementing Hyperdimensional Computing applications and need to significantly boost performance and reduce power consumption compared to traditional CPU-only approaches.
Not ideal if you are looking for a software-only solution or are not working with specialized hardware for accelerating AI workloads.
Stars
35
Forks
1
Language
C
License
MIT
Category
Last pushed
May 05, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/yuya-isaka/HPU"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
pymc-devs/pytensor
PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions...
arogozhnikov/einops
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
lava-nc/lava-dl
Deep Learning library for Lava
tensorly/tensorly
TensorLy: Tensor Learning in Python.
tensorpack/tensorpack
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility