LAB EDGE
AI Myanmar Research Infrastructure
Distributed LLM Benchmark & High-Throughput Ingestion Node
CONTINUOUS SYNC: ACTIVE
Active Shard Ingestion
↓ 1.2 MB/s
Full-Duplex WS Channel
Cumulative Volume (24h)
648.32 GB
Continuous Shard Ingestion
Pipeline Ingestion Task
Corpus Batch #41,208
Parquet Multi-tensor Stream
Total Sync Packets
84,192,401
Zero Packet Loss (Verified)
Distributed Edge Stream Log (Real-Time)
[System Initialization - Cluster Node 04]
• Host: lab.aimyanmar.website (Edge Gateway)
• Pipeline: Continuous Multi-Node Token & Tensor Ingestion
• Transport: Full-Duplex WSS over TLSv1.3 (Multiplexed High-Bandwidth)
• Active Task: Background Model Weights & Dataset Shard Sync Active.
Clear Output
🇲🇲 မြန်မာဘာသာ Model စမ်းသပ်ချက်
⚡ WS Stream Latency
🧠 Memory Buffer Test
Run
Model Topology
LOADED
Active Checkpoint
aimyanmar-llama-3-8b-my-instruct-q4
gemma-2-9b-burmese-tokenizer-v1
deepseek-coder-6.7b-edge-eval
Temperature
0.7
Live Hardware & Network Telemetry
AUTOSYNC
Node Cluster:
NVIDIA A100-SXM4
GPU Engine Load:
52%
VRAM Allocated:
54.8 / 80 GB
TTFT (Latency):
19ms
Stream Speed:
0.0 tokens/s
Active WS Ingestion:
16 Edge Shards