⚡ RingTheory: Energy-Efficient GPU Computing for Miners
🚀 PROVEN RESULTS:
After extensive testing on RTX 3090 (24GB), we achieved:
- Average 19.4% energy savings** across all matrix sizes
- Up to 59.4% energy savings** on 4096×4096 operations
- 7.99% average performance increase** (yes, faster AND more efficient!)
📊 TEST RESULTS (RTX 3090):| Matrix Size | Energy Savings | Speed Increase |
| 512×512 | -3.2% | +0.5% |
| 1024×1024 | +3.9% | +1.5% |
| 2048×2048 | +17.6% | +7.8% |
| 4096×4096 | +59.4% | +23.2% |
| 16384×16384 | +28.0% | +8.3% |
💰 BUSINESS CASE:
For 100 GPU mining farm:
- Monthly savings: $7,345
- Yearly savings: $88,134
- CO2 reduction: 294,000 kg/year
🛠️ HOW TO INSTALL:
## 🛠️ HOW TO INSTALL:
```bash
# Basic installation
pip install ringtheory
# For GPU mining optimization
pip install ringtheory[mining]
# For data center optimization
pip install ringtheory[gpu]
# QUICK START FOR MINERS:
python
from ringtheory import MiningOptimizer
import torch
optimizer = MiningOptimizer()
# Optimize mining operations
def optimized_mining_cycle(data):
tensor_data = torch.tensor(data, device='cuda')
optimized = optimizer.optimize_mining_operation(tensor_data, algorithm='ethash')
return optimized
# Monitor your savings
from ringtheory import EnergyMonitor
monitor = EnergyMonitor()
savings = monitor.measure_savings(duration=3600)
print(f"Energy saved: {savings['percentage']:.1f}%")
print(f"Money saved: ${savings['money_usd']:.2f}/hour")
Examples -
https://arkhipsoft.ru/Article/ID?num=89📦 PACKAGE FEATURES:
✅ Energy monitoring - Real-time power consumption tracking
✅ GPU optimization - Automatic ring pattern detection
✅ Multi-GPU support - Scale across mining farms
✅ Open source core - Free for personal/non-commercial use
✅ Commercial licenses - For mining farms/data centers
🔗 LINKS:
PyPI Package:
https://pypi.org/project/ringtheory/🎯 PERFECT FOR:
GPU Mining Farms
Crypto Miners
Data Centers
AI/ML Training Operations
Scientific Computing
💡 HOW IT WORKS:
RingTheory uses quantum-inspired ring patterns to optimize memory access, reduce cache misses, and minimize energy consumption while actually improving performance.
⚠️ IMPORTANT:
Free for personal/small-scale use (up to 2 GPUs)
Commercial licenses available for mining farms
📈 ROI CALCULATOR:
# Calculate your potential savings
from ringtheory import MiningROICalculator
calculator = MiningROICalculator()
savings = calculator.calculate(
gpu_count=100,
power_cost=0.15, # $ per kWh
avg_usage=24 # hours/day
)
print(f"Monthly savings: ${savings:.2f}")
🤝 SUPPORT:
Telegram: @vipvodu
Prove it yourself - test for 24 hours and see the savings!
Tested on: NVIDIA RTX 3090, 24GB VRAM, CUDA 11.7, Python 3.9+
Results may vary based on hardware and workload.*
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Perfect for: GPU miners, mining farms, data centers
#cryptomining #gpu #energyefficiency #python #bitcoin #ethereum
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