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207 results about "Address generation unit" patented technology

The address generation unit (AGU), sometimes also called address computation unit (ACU), is an execution unit inside central processing units (CPUs) that calculates addresses used by the CPU to access main memory. By having address calculations handled by separate circuitry that operates in parallel with the rest of the CPU, the number of CPU cycles required for executing various machine instructions can be reduced, bringing performance improvements.

Reconfigurable CNN (Convolutional Neural Network) high concurrency convolution accelerator

The invention provides a reconfigurable CNN (Convolutional Neural Network) high concurrency convolution accelerator, which comprises a weight address generation unit, a result address generation unit,a reconfigurable calculation unit, a characteristic pattern address generation unit, a master controller and a memory exchange unit, wherein the weight address generation unit generates the address of convolution kernel data in a cache; the result address generation unit generates the address of result data in the cache; the reconfigurable calculation unit can reconfigure a calculation array intotwo multiply-accumulation tree circuits with different particle sizes; the characteristic pattern address generation unit generates the address of characteristic pattern data in the cache; the mastercontroller generates an accumulator resetting signal synchronous with the address, carries out gating on a corresponding circuit in the reconfigurable calculation unit, and generates an interrupt signal for the end of the whole operation; and the memory exchange unit converts an effective characteristic pattern read address and a weight read address into the read operation of a memory unit, and converts an effective result write address and data into a write operation for the memory unit. The accelerator has the beneficial effects that a control part is simplified, the degree of parallelism of a multi-channel convolution operation and memory access efficiency can be greatly improved, and occupied resources are reduced.
Owner:NANJING UNIV
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