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

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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