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TetraMem Integrates Energy-Efficient In-Memory Computing with Andes RISC-V Vector Processor

By September 10, 2024No Comments1 min read
  • Marketing Specialist, RISC-V International

    Anisha is part of the RISC-V International marketing team, responsible for managing social media and tracking the latest updates from our members. She brings more than seven years of experience in digital marketing and communications strategy to the team.


The rapid proliferation of artificial intelligence (AI) across a growing number of hardware applications has driven an unprecedented demand for specialized compute acceleration not met by conventional von Neumann architectures. Among the competing alternatives, one showing the greatest promise is analog in-memory computing (IMC). Unleashing the potential of multi-level Resistive RAM (RRAM) is making the promise more real today than in the past. Leading this development, TetraMem, Inc., a Silicon Valley based startup, is addressing the fundamental challenges holding this solution back. The company’s unique IMC that employs multi-level RRAM technology provides more efficient, low-latency AI processing that meets the growing needs of modern applications in AR/VR, mobile, IoT, and beyond.

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