{"id":185973,"date":"2026-02-10T03:50:07","date_gmt":"2026-02-10T08:50:07","guid":{"rendered":"https:\/\/testing.news-you-need.com\/index.php\/2026\/02\/10\/bulk-rram-scaling-the-ai-memory-wall\/"},"modified":"2026-02-10T03:50:10","modified_gmt":"2026-02-10T08:50:10","slug":"bulk-rram-scaling-the-ai-memory-wall","status":"publish","type":"post","link":"https:\/\/testing.news-you-need.com\/index.php\/2026\/02\/10\/bulk-rram-scaling-the-ai-memory-wall\/","title":{"rendered":"Bulk RRAM: Scaling the AI Memory Wall"},"content":{"rendered":"

Bulk RRAM: Scaling the AI Memory Wall<\/a><\/p>\n

https:\/\/spectrum.ieee.org\/ai-and-memory-wall<\/a><\/p>\n

Publish Date: 2026-02-09 08:00:02<\/a><\/p>\n

Source Domain: spectrum.ieee.org<\/a><\/p>\n

A New Ray of Hope for AI: Overcoming the Memory Wall with Novel Resistive RAM<\/h2>\n

Researchers from the University of California, San Diego, presented a promising solution to enhance AI performance at the IEEE International Electron Device Meeting in December, by introducing an innovative type of Resistive RAM (RRAM) known as bulk RRAM. Current limitations in traditional RRAM, particularly the high voltage required to form data storage filaments, unstable resistance switching processes, and difficulty in stacking have impeded its integration and use in processors. The San Diego team designed bulk RRAM to switch entire layers of resistance, eliminating the need for filaments and the high-voltage step. They achieved compact, nanoscale RRAM devices that could be stacked in eight layers, demonstrating their potential in running complex matrix operations crucial for neural networks. The researchers stacked eight layers of bulk RRAM to form 1-kilobyte arrays and tested them with a continuous learning algorithm. The results showed 90% accuracy in classifying movements from wearable sensor data, proving the potential of this technology for edge AI applications where constant learning without cloud access is essential. <\/p>\n

Key Points:<\/h2>\n
    \n
  • Researchers developed a new type of Resistive RAM called bulk RRAM to overcome traditional RRAM’s limitations on AI performance.<\/li>\n
  • Bulk RRAM bypasses the high-voltage filament-forming step, enabling a nanoscale design stackable in multiple layers with enhanced resistance ranges.<\/li>\n
  • The new technology demonstrated 90% accuracy in a continuous learning algorithm to classify sensor data, promising its utility for edge devices in AI.<\/li>\n
  • While promising, data retention at operating temperatures remains a challenge for integration into real-world computing systems.<\/li>\n
  • Bulk RRAM holds significant potential to bridge the memory wall gap for AI, as traditional memory systems struggle to keep up with large model requirements.<\/li>\n<\/ul>\n

    <\/p>\n","protected":false},"excerpt":{"rendered":"

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