In a new partnership, decentralized GPU compute network, io.net has announced its collaboration with ParallelAI, a leader in parallel processing optimization for AI developers. This partnership will enable ParallelAI to integrate io.net’s decentralized GPU clusters into its platform, enhancing the computing capacity required for large-scale AI tasks.
GPU Resources Expansion for AI Developers
ParallelAI currently accesses GPU resources through 10 Cloud, utilizing A100 GPUs for complex tasks like large language model (LLM) training, inference, and distributed deep learning. Without traditional infrastructure constraints, ParallelAI can scale its services and better meet AI developers’ demands. This partnership is set to expand the GPU computing available to AI developers and researchers.
io.net and ParallelAI will also focus on joint research and development. Together, they aim to push the boundaries of decentralized GPU cloud computing and develop advanced technologies that could redefine performance standards in the AI sector.
io.net Streamlining AI Development with ParallelAI
ParallelAI helps AI developers write high-level code by optimizing computing processes across multiple GPUs and CPUs, cutting computation time by up to 20x. This reduces costs and infrastructure needs. Through io.net’s decentralized clusters, ParallelAI can offer more scalable, flexible, and reliable GPU access for developers working on complex AI workloads while minimizing potential bottlenecks.
ParallelAI clients can benefit from the cost savings provided by io.net’s decentralized model, which sources GPU resources from various locations. This model can lower costs compared to centralized cloud providers, offering up to 90% savings. The partnership allows ParallelAI to tap into a wider share of the AI/ML developer market while avoiding costly hardware investments.
