Annapurna Labs: AWS Custom Silicon | Generated by AI
What is Annapurna Labs?
Annapurna Labs is an Israeli semiconductor company specializing in high-performance, energy-efficient processors for cloud computing, networking, storage, and AI workloads. It was acquired by Amazon in January 2015 for a reported ~$350–370 million and now operates as a wholly-owned subsidiary of Amazon Web Services (AWS).
Annapurna Labs designs custom silicon that powers much of AWS’s infrastructure, enabling Amazon to reduce reliance on third-party chip vendors like Intel, Broadcom, and NVIDIA for certain workloads.
Key Chips Designed by Annapurna Labs (Used in AWS)
| Chip Family | Type | Key Features | Primary AWS Use Case |
|---|---|---|---|
| Alpine | ARM-based SoC | Multi-core ARMv8 CPUs, low power, integrated networking/storage | Early EC2 instances, storage controllers |
| Graviton | ARM-based CPU | 64-bit ARM Neoverse cores (AWS-designed), high core count, DDR5, PCIe Gen4/5 | EC2 Graviton instances (general-purpose compute) |
| Nitro | SmartNIC / Offload | ARM CPUs + custom accelerators for virtualization, security, storage, networking | EC2 Nitro System, EBS, VPC, security offload |
| Inferentia | AI Inference | High-throughput tensor processing, low latency, neuron cores | EC2 Inf1/Inf2 instances for ML inference |
| Trainium | AI Training | Scalable for large language models, high memory bandwidth, NeuronLink interconnect | EC2 Trn1/Trn2 instances for training LLMs |
Flagship Chip Families (Current as of 2025)
1. AWS Graviton (CPU)
- Architecture: Custom ARM Neoverse-based cores (not off-the-shelf)
- Generations:
- Graviton1 (2018): 16-core ARMv8, used in A1 instances
- Graviton2 (2020): 64-core Neoverse N1, ~40% better price/perf than x86
- Graviton3 (2022): Neoverse V1, DDR5, bfloat16, up to 60% better than Graviton2
- Graviton4 (2024): Neoverse V2, 96 cores, 2.7x perf/W over Graviton3
- Use: Powers ~30–40% of AWS EC2 workloads (especially containers, microservices, databases)
2. AWS Inferentia (AI Inference)
- Inferentia2 (2023): 4x performance over Inferentia1, supports FP16/BF16/INT8
- Optimized for real-time inference (recommendation engines, speech, vision)
- Used in SageMaker, EC2 Inf2
3. AWS Trainium (AI Training)
- Trainium2 (announced 2024, shipping 2025): 4x training perf over Trainium1
- Designed to compete with NVIDIA H100 for LLM training
- Supports trillion-parameter models, high-bandwidth memory (HBM)
4. Nitro System (SmartNIC / DPU)
- Custom ARM SoCs with hardware accelerators
- Offloads hypervisor, networking, storage, encryption
- Enables bare-metal performance in virtualized environments
Why Annapurna Matters
- Cost & Efficiency: AWS claims up to 40% better price/performance vs x86
- Vertical Integration: Amazon controls silicon → faster innovation, lower costs
- AI Push: Trainium/Inferentia directly challenge NVIDIA’s dominance in cloud AI
- Supply Chain Resilience: Reduces dependency on Intel/TSMC-only supply
Summary
Annapurna Labs = AWS’s secret silicon weapon.
They build ARM-based Graviton CPUs, Inferentia (inference), Trainium (training), and Nitro offload chips — all optimized for the cloud.
These power cheaper, faster, greener AWS services and are a key reason AWS can undercut competitors on price while scaling AI.
Let me know if you want deep dives into any specific chip (e.g., Graviton4 vs Apple M4, Trainium2 vs H100).