1 Repo
Awesome GitHub RepositoriesMulti-Backend Execution
Computational execution that distributes workloads across heterogeneous hardware engines.
Distinct from Parallel Processing: Focuses on distributing AI workloads across different hardware backends (CPU/GPU) rather than generic data-parallel processor cores.
Explore 1 awesome GitHub repository matching data & databases · Multi-Backend Execution. Refine with filters or upvote what's useful.
Awesome Multi-Backend Execution GitHub Repositories
Finde die besten Repos mit KI.Wir suchen mit KI nach den am besten passenden Repositories.
- nervanasystems/neon
NervanaSystems/neon
3,864Auf GitHub ansehenNeon is a deep learning framework and hardware-abstraction machine learning stack used for designing, training, and deploying neural network architectures. It functions as a graph-based computation engine that utilizes just-in-time kernel compilation to optimize machine code for tensors. The platform decouples model definitions from execution kernels, allowing it to support multiple CPU and GPU backends. This architecture enables the distribution of computational workloads across parallelized hardware environments to increase processing speed and overall efficiency. The system covers the ful
Distributes computational workloads across parallelized hardware environments to increase training speed and efficiency.
Python
