Helping data centers deliver higher performance with less hardware

2026-04-07 · Source: MIT News - Artificial intelligence · Field: Technology & Digital — Cloud Computing & IT Infrastructure, Artificial Intelligence & Machine Learning · Depth: Intermediate, medium

Summary

MIT researchers have developed Sandook, a software-based system designed to enhance the efficiency and longevity of flash storage hardware in data centers. Published on April 7, 2026, Sandook addresses three major sources of performance variability in Solid-State Drives (SSDs): differences in hardware (age, wear, capacity), read-write operation mismatches, and unpredictable garbage collection processes. The system employs a two-tier architecture with a global scheduler for overall task distribution and local controllers for rapid, real-time data rerouting. When tested on realistic tasks like AI model training and image compression, Sandook nearly doubled performance compared to traditional methods, boosting throughput by 12-94% and improving SSD capacity utilization by 23%, achieving 95% of theoretical maximum performance without specialized hardware.

Key takeaway

For CTOs and VPs of Engineering evaluating data center infrastructure upgrades, Sandook demonstrates that significant performance gains and extended hardware lifespan are achievable through intelligent software solutions. You can nearly double throughput and improve SSD utilization by 23% without investing in new hardware, directly impacting operational costs and sustainability goals. Consider integrating advanced workload balancing systems to maximize your current flash storage investments.

Key insights

Sandook intelligently balances SSD workloads to significantly boost data center performance and extend hardware lifespan without new equipment.

Principles

• Address multiple variability sources simultaneously for optimal gains.
• Combine global optimization with local, real-time adaptation.
• Maximize existing hardware performance before replacement.

Method

Sandook uses a two-tier architecture: a global scheduler for task distribution and local controllers for real-time data rerouting, adapting to read-write interference and garbage collection by profiling SSD performance and adjusting workloads dynamically.

In practice

• Implement software-defined storage solutions for existing SSD pools.
• Profile individual SSD performance to inform workload assignments.
• Prioritize solutions that extend hardware longevity.

Topics

• Sandook System
• Data Center Efficiency
• Flash Storage Optimization
• SSD Performance Variability
• Workload Balancing

Code references

• mit-sandook/sandook

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Engineer, MLOps Engineer, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by MIT News - Artificial intelligence.