INDUSTRY COMPONENT

On-Chip Memory

On-chip memory is integrated memory directly on a neural processing unit die for high-speed data access.

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Component Specifications

Definition
On-chip memory refers to memory components fabricated directly on the same semiconductor die as the neural processing unit (NPU) processor cores. This integrated architecture provides ultra-low latency and high-bandwidth data access for neural network computations, eliminating the need for external memory interfaces during critical operations. It typically includes SRAM (Static Random-Access Memory) blocks organized in hierarchical structures (L1/L2 caches, scratchpad memory) optimized for tensor operations and weight storage in AI workloads.
Working Principle
On-chip memory operates by storing data in SRAM cells within the NPU die, using flip-flop circuits that maintain data as long as power is supplied. It employs memory controllers and interconnect fabrics to manage data movement between processor cores and memory banks. The working principle involves low-latency access through dedicated memory buses, cache coherence protocols for multi-core NPUs, and memory partitioning for simultaneous access to weights, activations, and intermediate results during neural network inference and training.
Materials
Silicon substrate with CMOS technology, copper interconnects, high-k metal gate transistors, silicon dioxide or advanced low-k dielectric insulation layers. Fabricated using semiconductor processes (e.g., 7nm, 5nm FinFET nodes) with multiple metal layers for routing.
Technical Parameters
  • Latency 1-10 ns
  • Voltage 0.7-1.0V
  • Capacity 1-128 MB
  • Bandwidth 100-1000 GB/s
  • Technology Node 7nm-5nm
  • Operating Temperature -40°C to 125°C
Standards
ISO 26262, JEDEC JESD209

Industry Taxonomies & Aliases

Commonly used trade names and technical identifiers for On-Chip Memory.

on-chip memory NPU memory AI memory neural network memory SRAM for NPU embedded memory high-bandwidth memory low-latency memory On-Chip Memory in Computer, Electronic and Optical Product Manufacturing

Parent Products

This component is used in the following industrial products

Neural Processing Unit

A specialized hardware accelerator designed to efficiently process artificial neural network algorithms and machine learning workloads.

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Engineering Analysis

Risks & Mitigation
  • Thermal-induced data corruption
  • Process variation affecting yield
  • Soft errors from radiation
  • Voltage droop causing access failures
FMEA Triads
Trigger: Electromigration in interconnects
Failure: Increased resistance leading to timing violations
Mitigation: Use redundant vias and thicker metal layers
Trigger: Alpha particle strikes
Failure: Bit flips in SRAM cells (soft errors)
Mitigation: Implement error-correcting codes (ECC) and parity checking
Trigger: Power supply noise
Failure: Memory access failures during high-frequency operation
Mitigation: Design robust power delivery networks with decoupling capacitors

Industrial Ecosystem

Compatible With

Interchangeable Parts

Compliance & Inspection

Tolerance
±5% for timing parameters, ±10% for voltage levels
Test Method
Automated test equipment (ATE) with memory BIST (Built-In Self-Test), shmoo plots for parametric testing, and functional verification with AI workloads

Procurement Evaluation Criteria

Not customer reviews or live demand data. These dimensions support RFQ preparation and supplier evaluation.

Technical documentation
4/5
Manufacturing capability
4/5
Inspection readiness
5/5
Supplier transparency
3/5

These scores are example evaluation dimensions, not real customer ratings, country-specific buyer feedback, or live inquiry activity.

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Frequently Asked Questions

What is the difference between on-chip memory and off-chip memory in NPUs?

On-chip memory is integrated directly on the NPU die, offering nanosecond latency and terabyte-per-second bandwidth, while off-chip memory (like DDR or HBM) is external, with higher latency but larger capacity.

Why is on-chip memory critical for neural processing units?

It reduces data movement bottlenecks, enabling faster access to weights and activations, which improves energy efficiency and throughput in AI computations.

Can on-chip memory be upgraded or expanded?

No, on-chip memory capacity is fixed during manufacturing as part of the NPU's semiconductor design and cannot be modified after production.

Can I contact factories directly?

Yes, each factory profile provides direct contact information.

Data Basis

CNFX manufacturer profiles, technical classification, publicly available product information, and ongoing plausibility checks.

Preliminary Technical Classification
This page supports structured research, RFQ preparation, and supplier evaluation. It does not replace buyer-led supplier qualification, standards review, or technical approval.

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