Sambanova Systems, Inc.

Chen Liu

Sumti Jairath

Arvind Krishna Sujeeth

Junjue Wang

Zhuo Chen

Bowen Yang

Blaine Rister

Qingjian Li

Fei Wang

Venkat Krishna Srinivasan

In a method, in response to an interface a computer-implemented analysis assistant initiates a presentation of inefficiency results, determined an efficiency analyzer based on a mapping of a dataflow program to execute on hardware of a computing system. The assistant receives an inefficiency included among the inefficiency results and composes formatted inefficiency results comprising a presentation format of the inefficiency to assist a developer of the dataflow program to interpret the inefficiency. The analysis assistant outputs the formatted inefficiency results to an interface, which can comprise an interface to output the formatted inefficiency results for use by the developer to improve the dataflow program in association with the inefficiency. In implementations the presentation can comprise an interactive presentation with a developer of the dataflow program. A computer program product and a computing system can implement the method. The computing system can execute the assistant, and can include the interfaces.

Analysis assistant for determining execution inefficiencies in dataflow programs

In a method a computer-implemented efficiency analyzer selects operators from an intermediate representation of a dataflow program. The operators are included in a mapping of the operators to hardware of a computing system to execute the dataflow program. Based on the mapping and a description of the hardware, the efficiency analyzer computes an execution metric associated with executing the operators on the hardware. Based on the execution metric and hardware description, the efficiency analyzer determines an inefficiency metric, and based on the inefficiency metric, the efficiency analyzer determines an inefficiency associated with the dataflow program. The computing system to execute the dataflow program can comprise a coarse grain computing system and the hardware can include a reconfigurable processor of the computing system. A computer program product and a computing system to a the dataflow program can implement the method.

Method and system to determine execution inefficiencies in dataflow programs

According to a computing method a compiler determines a recompute node included in a dataflow application and a checkpoint tensor produced by the recompute node. The compiler determines a recompute cost to recompute the checkpoint tensor, and a memory cost to checkpoint the checkpoint tensor in a memory. Based on the recompute cost and/or the memory cost, the compiler determines a solution cost and compares the solution cost to a solution threshold. Based on comparing the solution cost to the solution threshold, the compiler determines a checkpoint solution to execute the dataflow application. The checkpoint solution can comprise recomputing or checkpointing the checkpoint tensor. In some implementations, the compiler can determine a recompute ratio of the recompute cost to the memory cost and can compare the recompute ratio to the solution threshold. A computer program product and a computing system can implement aspects of the method.

Tensor checkpoint optimization in dataflow computing applications

A computation unit comprises first, second, and third circuits. The first circuit traverses gradient loss elements gand normalized output elements pand produces an accumulation C. The accumulation C is produced by element-wise multiplying the gradient loss elements gwith the corresponding normalized output elements pand summing the results of the element-wise multiplication. The second circuit, operatively coupled to the first circuit, element-wise subtracts the accumulation C from each of the gradient loss elements gand produces modulated gradient loss elements g. The third circuit, operatively coupled to the second circuit, traverses the modulated gradient loss elements gand produces gradient loss elements gfor a function preceding the softmax function. The gradient loss elements gare produced by element-wise multiplying the modulated gradient loss elements gwith the corresponding normalized output elements p.

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Palo Alto, CA, United States of America

Chen Liu