Tensor parallelism is all you need. Run LLMs on weak devices or make powerful devices even more powerful by distributing the workload and dividing the RAM usage.
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Updated
Jun 1, 2024 - C++
Tensor parallelism is all you need. Run LLMs on weak devices or make powerful devices even more powerful by distributing the workload and dividing the RAM usage.
Short self-contained descriptions of distributed algorithms suitable for 2nd year undergraduates.
The current, performant & industrial strength version of Holochain on Rust.
The open-source serverless GPU container runtime.
Distributed model training and inference for PyTorch.
Prime95 source code from GIMPS to find Mersenne Prime.
Tensorlink is a distributed computing framework based on CUDA API-Forwarding
The library for developing distributed Erlang applications
Unleash the power of cloud
A distributed task scheduler for Dask
Modular, Scalable Phenomic Data Processing Pipelines
Distributed DataFrame for Python designed for the cloud, powered by Rust
This program simulates a distributed load balancers that channels circle to radius traffic on distributed servers.
Distributed computing is the field of study that deals with the division of tasks between multiple computers connected in a network.
Backend.AI is a streamlined, container-based computing cluster platform that hosts popular computing/ML frameworks and diverse programming languages, with pluggable heterogeneous accelerator support including CUDA GPU, ROCm GPU, TPU, IPU and other NPUs.
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Python Wrapper for Message-Oriented and Robotics Middleware
Distributed Stockfish analysis for lichess.org
zenoh unifies data in motion, data in-use, data at rest and computations. It carefully blends traditional pub/sub with geo-distributed storages, queries and computations, while retaining a level of time and space efficiency that is well beyond any of the mainstream stacks.
JAnelia Compute Services (JACS)
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