Render Network | RNDR - Announcements ✔

RNP-005 is live! https://github.com/rendernetwork/RNPs/blob/main/RNP-005.md

This proposal outlines onboarding Beam as the second Compute Client to leverage Render Network's GPU supply for machine learning workloads.

Beam provides a cloud platform to accelerate AI development and deployment using GPUs without managing infrastructure. Key capabilities include:

Local Python development with remote execution on cloud GPUs

Dynamic cluster orchestration by specifying GPU types/counts, libraries

Auto-scaling of GPU instances based on workload demand

Serverless deployment via REST APIs, cron jobs, task queues

Distributed storage volumes attached to containers

SDKs for CI/CD integration and tooling

Integrating Beam enables the Render Network's decentralized GPU network to power these ML-focused workloads. Beam clusters will be able to access the Render Network's global supply of GPUs tailored for parallelized AI computations.

Snapshot voting for the Initial Proposal Vote open for 72 hours:
https://snapshot.org/#/rndrnetwork.eth/proposal/0x559c0edba0daea7b2a8ff4555a8a119b9ba0185ebbf0ad799a1f21781f71ca19

GitHub

RNPs/RNP-005.md at main · rendernetwork/RNPs

The Render Network Proposal Repository. Contribute to rendernetwork/RNPs development by creating an account on GitHub.

www.tgoop.com/rendertoken/494

6.08K viewsOct 23, 2023 at 20:14

RNP-005 is live! https://github.com/rendernetwork/RNPs/blob/main/RNP-005.md

This proposal outlines onboarding Beam as the second Compute Client to leverage Render Network's GPU supply for machine learning workloads.

Beam provides a cloud platform to accelerate AI development and deployment using GPUs without managing infrastructure. Key capabilities include:

Local Python development with remote execution on cloud GPUs

Dynamic cluster orchestration by specifying GPU types/counts, libraries

Auto-scaling of GPU instances based on workload demand

Serverless deployment via REST APIs, cron jobs, task queues

Distributed storage volumes attached to containers

SDKs for CI/CD integration and tooling

Integrating Beam enables the Render Network's decentralized GPU network to power these ML-focused workloads. Beam clusters will be able to access the Render Network's global supply of GPUs tailored for parallelized AI computations.

Snapshot voting for the Initial Proposal Vote open for 72 hours:
https://snapshot.org/#/rndrnetwork.eth/proposal/0x559c0edba0daea7b2a8ff4555a8a119b9ba0185ebbf0ad799a1f21781f71ca19

BY Render Network | RNDR - Announcements