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HYPERACCEL TECH BLOG

From transistors to LLM inference,
we write about full-stack AI.

Chip design, memory, compilers, infrastructure, and models. HyperAccel engineers write down what they learn across every layer of the AI stack.

Latest

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AI Hardware

Architecture deep dives on AI accelerators: GPU, TPU, LPU, wafer-scale chips, and CPUs.

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Memory & Storage

The memory hierarchy of the AI era: HBM, HBF, CXL, and KV-cache storage tiers.

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Compilers & Kernels

The software stack above the silicon: compiler theory, torch.compile, custom kernels, and Legato.

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LLM & Models

Transformer internals, serving frameworks, and analyses of recent models.

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Infra & DevOps

How HyperAccel builds its infrastructure: Kubernetes dev environments, CI/CD, device plugins.

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Engineering Culture

How we work: AI coding agents, development methodologies, and running this tech blog.

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Conference Reports

Field reports from CES, NAVER DAN, PyTorch Conference, and more.

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Semiconductor

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Programming Language

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