
Mainframe
Loading...
Market Cap
Loading...
24h Trading Vol
Loading...
All Time High
Loading...
All Time Low
Loading...
Total Supply
Loading...
Max Supply
Loading...
Circulating Supply
Loading...
Categories
Chains
N/AContracts

FAQs
What is Mainframe and how does it work?
Mainframe (SN25) is a Bittensor subnet dedicated to protein folding using distributed compute. It leverages the industry-standard GROMACS software and CUDA-supported GPUs. Miners compete to provide protein configurations that coincide with the lowest energy, which aligns with the goal of creating biologically stable structures. The Macrocosmos SDK provides the Mainframe API to submit protein folding jobs and perform simulations, generating valuable datasets for AI model training and scientific research.
What problem does Mainframe solve?
Mainframe addresses the high cost and centralized compute associated with complex scientific problems like protein folding. By incentivizing a distributed network of miners, SN25 drives down the cost per query, making protein folding more accessible to scientists. This democratizes access to powerful tools, accelerates research, and facilitates breakthroughs in drug discovery by utilizing a decentralized system compared to a centralized system such as AlphaFold3.
How does Mainframe differ from competitors?
Mainframe distinguishes itself by utilizing a competitive, incentivized network built on the Bittensor protocol for protein folding. This approach motivates miners to relentlessly improve their protein-folding machine learning models, reducing compute costs while improving performance. Unlike centralized solutions, Mainframe offers a transparent and deterministic system, aligning the incentives of miners with the desired outcome of biologically stable protein structures, all while being accessible on the blockchain.
How does SN25 ensure the scientific accuracy of its protein folding results?
SN25 employs three verification mechanisms: (1) Cross-validation by independent validator nodes comparing results against known protein structures; (2) Energy minimization thresholds that must meet biophysical stability criteria; (3) Deterministic MD algorithms producing reproducible trajectories. Validators use statistical consensus models to identify outliers, with malicious actors penalized through slashing.
What hardware requirements exist for participating as a miner in SN25?
Miners require: (1) CUDA-compatible GPUs (minimum 8GB VRAM); (2) Containerization support (Docker); (3) Stable high-bandwidth internet connection. The base implementation utilizes NVIDIA's cuMM libraries optimized for molecular dynamics. While consumer-grade hardware can participate, competitive miners typically deploy server-grade GPUs (A100/H100) due to computational intensity.
How does SN25 compare to traditional cloud computing for scientific workloads?
SN25 offers: (1) Cost efficiency through competitive resource pricing, (2) Specialized infrastructure for MD simulations, (3) Transparent methodology unlike proprietary black-box solutions. Unlike generalized cloud compute, SN25's architecture minimizes data transfer overhead through specialized containers and avoids centralized vendor lock-in. Performance benchmarks show 3-5x cost advantage versus AWS for comparable protein folding tasks.
Can academic researchers use SN25 without cryptocurrency expertise?
Yes, through the Organic API which provides: (1) Traditional REST endpoints, (2) TAO-denominated billing abstraction, (3) Python/JS client libraries. Researchers submit PDB files and receive simulation results without directly handling blockchain transactions. The system automatically converts fiat payments to TAO using integrated gateways, making it accessible to non-crypto-native scientists.
How does SN25 prevent intellectual property exposure in commercial research?
The network implements: (1) End-to-end encryption for all protein structure submissions, (2) Zero-knowledge proof techniques allowing validation without raw data exposure, (3) Optional trusted execution environments (TEEs) for sensitive workflows. Commercial partners like Rowan Scientific use private subnet instances for proprietary research while contributing to public network validation.