Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing integrated circuit architectures or compiler designs using an optimization engine. The optimization engine includes an auto-encoder and one or more regressors. Once trained, the optimization engine can encode initial, discrete input values of a set of input characteristics into a continuous domain and use continuous optimization techniques to identify final input values of the set of input characteristics that optimize one or more output characteristics.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for jointly determining neural network architectures and hardware accelerator architectures.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining architectures of hardware accelerators.

Abstract: A computing system for performing distributed large scale reinforcement learning with improved efficiency can include a plurality of actor devices, wherein each actor device locally stores a local version of a machine-learned model, wherein each actor device is configured to implement the local version of the machine-learned model at the actor device to determine an action to take in an environment to generate an experience, a server computing system configured to perform one or more learning algorithms to learn an updated version of the machine-learned model based on the experiences generated by the plurality of actor devices, and a hierarchical and distributed data caching system including a plurality of layers of data caches that propagate data descriptive of the updated version of the machine-learned model from the server computing system to the plurality of actor devices to enable each actor device to update its respective local version of the model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing integrated circuit architectures or compiler designs using an optimization engine. The optimization engine includes an auto-encoder and one or more regressors. Once trained, the optimization engine can encode initial, discrete input values of a set of input characteristics into a continuous domain and use continuous optimization techniques to identify final input values of the set of input characteristics that optimize one or more output characteristics.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing integrated circuit architectures or compiler designs using an optimization engine. The optimization engine includes an auto-encoder and one or more regressors. Once trained, the optimization engine can encode initial, discrete input values of a set of input characteristics into a continuous domain and use continuous optimization techniques to identify final input values of the set of input characteristics that optimize one or more output characteristics.

Abstract: A random access memory may include memory banks and arithmetic approximation units. Each arithmetic approximation unit may be dedicated to one or more of the memory banks and include a respective multiply-and-accumulate unit and a respective lookup-table unit. The respective multiply-and-accumulate unit is configured to iteratively perform shift and add operations with two inputs and to provide a result of the shift and add operations to the respective lookup-table unit. The result approximates or is a product of the two inputs. The respective lookup-table unit is configured produce an output by applying a pre-defined function to the result. The arithmetic approximation units are configured for parallel operation. The random access memory may also include a memory controller configured to receive instructions, from a processor, regarding locations within the memory banks from which to obtain the two inputs and in which to write the output.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing integrated circuit architectures or compiler designs using an optimization engine. The optimization engine includes an auto-encoder and one or more regressors. Once trained, the optimization engine can encode initial, discrete input values of a set of input characteristics into a continuous domain and use continuous optimization techniques to identify final input values of the set of input characteristics that optimize one or more output characteristics.

Abstract: The prediction of memory failure is obtained by reducing the voltage on a bank of memory cells to momentarily artificially age the memory cells and subjecting the memory cells to a test in which one or more predetermined vectors are written to and read from the memory cells to detect memory cell errors.

Abstract: The prediction of memory failure is obtained by reducing the voltage on a bank of memory cells to momentarily artificially age the memory cells and subjecting the memory cells to a test in which one or more predetermined vectors are written to and read from the memory cells to detect memory cell errors.