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Reduced overall system cost and power consumption achieved with the use of 1.2-V VIO SPI NOR Flash

Modern NOR flash requires 1.8V, while contemporary SoCs on sub-10-nm nodes now function at 1.2V, necessitating a switch to a 1.2V input interface.

Reducing overall system cost and power consumption through the utilization of 1.2-V VIO SPI NOR...
Reducing overall system cost and power consumption through the utilization of 1.2-V VIO SPI NOR Flash technology.

Reduced overall system cost and power consumption achieved with the use of 1.2-V VIO SPI NOR Flash

In the realm of modern electronics, power efficiency and performance are paramount, especially in emerging sectors like edge AI, automotive, clean energy, and connectivity. A new development in flash memory technology, a dual-voltage SPI NOR flash architecture with a 1.8 V core supply and a 1.2 V I/O interface, is making waves for its ability to optimize compatibility with low-voltage SoCs, reduce power consumption, and enhance performance.

Advanced SoCs operate at voltages of 1.2 V or lower, but supporting higher-voltage I/O structures like 1.8 V can increase die size and cost. To bridge this gap, the dual-voltage approach offers a solution. By operating the I/O interface at 1.2 V, closer to advanced SoC operating voltages, it significantly reduces I/O power consumption and standby current. For instance, current draw can drop to as low as 12 µA in standby and 200 nA in deep power-down modes, lowering overall system power needs.

The 256-byte page program time improves to approximately 0.15 ms, which is around 40% faster than conventional 1.8 V SPI NOR flash devices. This allows faster firmware updates and real-time processing critical in automotive and edge AI scenarios. While the 1.2 V I/O enables lower power interface signaling, throughput benefits are also driven by serial NOR flash interface advances such as Quad and Octal SPI. These interfaces achieve up to 400 MB/s read bandwidth, facilitating faster boot times and richer code execution for domain controllers and sensor fusion systems prevalent in automotive and industrial IoT. Dual QSPI and DDR modes further enhance throughput and memory bus efficiency.

This architecture substantially benefits applications requiring low power, high-speed read/program operations, and enhanced throughput with improved energy efficiency—critical factors for the evolving demands of edge AI, automotive safety systems, clean energy management, and connected IoT devices.

| Parameter | Traditional 1.8 V SPI NOR Flash | Dual-Voltage (1.8 V core / 1.2 V I/O) SPI NOR Flash | |------------------------|----------------------------------------|-------------------------------------------------------------| | Read Power | Higher, due to 1.8 V I/O signaling | Lower, standby ~12 µA; deep power-down ~200 nA[1] | | Page Programming Speed | Baseline (~0.25 ms for 256 bytes approx.) | ~40% faster, ~0.15 ms for 256 bytes[1] | | Data Throughput | Quad SPI, Octal SPI up to ~400 MB/s | Supports same interfaces with lower power interface voltage; Dual QSPI & DDR options enhance throughput[2][4][5] |

The dual-voltage approach aligns with emerging SoC process nodes (10 nm and below) and voltage scaling trends, improving energy efficiency and performance without increasing SoC die size or complexity. This makes it particularly suitable for edge AI, automotive (including safety-critical ASIL-D systems), clean energy, and connectivity products demanding low power, high reliability, and fast code execution.

[1] GigaDevice GD25NE SPI NOR Flash Datasheet [2] GigaDevice GD25NE SPI NOR Flash Quad SPI Feature Datasheet [3] GigaDevice GD25NE SPI NOR Flash Octal SPI Feature Datasheet [4] GigaDevice GD25NE SPI NOR Flash Dual QSPI Feature Datasheet [5] GigaDevice GD25NE SPI NOR Flash DDR Feature Datasheet

Data-and-cloud computing relies heavily on technology, and this new development in flash memory technology, a dual-voltage SPI NOR flash architecture, is a testament to that. Its ability to optimize compatibility with low-voltage SoCs, reduce power consumption, and enhance performance makes it an essential piece of technology in the evolving data-and-cloud landscape, particularly in sectors like edge AI, automotive, clean energy, and connectivity.

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