Stacked apparatus using in-memory compute chiplet devices for inference-time compute acceleration
Assigneed-MATRIX CORPORATION
InventorsSudeep BHOJA, Siddharth SHETH
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Assigneed-MATRIX CORPORATION
InventorsSudeep BHOJA, Siddharth SHETH
Estimating the term…
A stacked apparatus using in-memory compute (IMC) chiplet devices for inference-time compute acceleration. The apparatus is configured to accelerate the workload computations for neural network models, such as those for Large Language Models (LLMs) and reasoning models. The apparatus achieves high throughput and low latency using a chiplet design, digital IMC (DIMC) based engines, efficient die-to-die (D2D) interconnects, block floating point (BFP) numerics, and large high bandwidth on-chip memories. With modular chiplets in stacked configurations with memory devices and efficient interconnects, the accelerator apparatus can be easily scaled to accelerate workloads for models of different sizes. The DIMC configuration within the chiplet slices also improves computational performance and reduces power consumption by integrating computational functions and memory fabric. And by dynamically switching between precision levels based on real-time analysis of a target workload, computational efficiency can be optimized while maintaining accuracy.
A stacked in-memory compute (IMC) accelerator apparatus comprising:
A stacked in-memory compute (IMC) accelerator apparatus comprising:
A stacked in-memory compute (IMC) apparatus comprising:
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