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9 articles
Scaling Llama 3: Meta’s 3,000km Lossless Multi-Datacenter Training
Imagine you are orchestrating a symphony. Now imagine that half of your violin section is in Virginia, your cellos are in Oregon, and the conductor is hovering…
Multi-Tenant Inference Graphs: Replacing the Static Endpoint
It was only eighteen months ago that "deploying an LLM" meant wrapping a Hugging Face checkpoint in a Flask API, shoving it onto a single A100, and praying the…
Vaporizing the GC Tax with CXL-Accelerated Memory
Imagine it’s 3:00 AM. You’re on-call for a global payments gateway. Suddenly, your $P{99}$ latency dashboards for the core Java microservices start bleeding re…
Smashing the Bandwidth Wall with Silicon Photonics and Software-Defined Fabrics
Imagine you’re standing in the middle of a modern hyperscale data center—a cathedral of silicon and steel. You’re surrounded by rows of racks, each housing H10…
Scaling LLM Training via Ethernet Without the InfiniBand Tax
In the high-stakes world of Large Language Model (LLM) training, we are currently witnessing a hardware arms race that would make the Cold War look like a scho…
Taming Non-Determinism in Large-Scale AI Training
Imagine this: You are three weeks into a training run for a next-generation Large Language Model. The compute cluster is a sprawling metropolis of tens of thou…
Scaling Netflix via Global Federated Kubernetes Mesh
It’s 8:00 PM on a Friday night. A new season of a global hit series has just dropped. Millions of users across six continents simultaneously hit the "Play" but…
NVLink 4.0 and the Dawn of Rack-Scale AI
The year is 2024, and the "Scale is All You Need" mantra has shifted from a research hypothesis to an industrial imperative. We are no longer debating whether…
Polaris Paradigm: Architecting Hyper-Elastic State via Shared Logs
In the early days of distributed systems, we were taught a fundamental lie: that compute and storage must live together to be fast. The "Data Locality" mantra…