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Cambricon: load-store instruction set for diverse neural workloads

Contribution grade

Neural-accelerator instruction sets · Human-designed research method or resource

Reference score135,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Specified scalar/vector/matrix, logical, control and transfer instructions with programmer-visible scratchpads, allowing multiple neural-network techniques to share a compact accelerator ISA.

Scientific scope

Specified scalar/vector/matrix, logical, control and transfer instructions with programmer-visible scratchpads, allowing multiple neural-network techniques to share a compact accelerator ISA. Inherits RISC/load-store, vector operations and prior NN accelerators. The evaluation covers ten chosen neural techniques and a65nm implementation prototype, not all future networks or identical latency/energy on every workload. Operands remain bounded by scratchpad capacity and larger operations require compiler tiling. Cambricon affiliation does not retroactively turn the earlier ICT–Inria DianNao work into a company product.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Inherits RISC/load-store, vector operations and prior NN accelerators. The evaluation covers ten chosen neural techniques and a65nm implementation prototype, not all future networks or identical latency/energy on every workload. Operands remain bounded by scratchpad capacity and larger operations require compiler tiling. Cambricon affiliation does not retroactively turn the earlier ICT–Inria DianNao work into a company product.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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