公开(公告)号：US20190114533A1

公开(公告)日：2019-04-18

申请号：US15785679

申请日：2017-10-17

Applicant: Xilinx, Inc.

Inventor： Aaron Ng ,  Jindrich Zejda ,  Elliott Delaye ,  Xiao Teng ,  Sonal Santan ,  Soren T. Soe ,  Ashish Sirasao ,  Ehsan Ghasemi ,  Sean Settle

IPC: G06N3/063 ,  G06N3/10 ,  G06N3/04 ,  G06N3/08

Abstract: Embodiments herein describe techniques for interfacing a neural network application with a neural network accelerator using a library. The neural network application may execute on a host computing system while the neural network accelerator executes on a massively parallel hardware system, e.g., a FPGA. The library operates a pipeline for submitting the tasks received from the neural network application to the neural network accelerator. In one embodiment, the pipeline includes a pre-processing stage, an FPGA execution stage, and a post-processing stage which each correspond to different threads. When receiving a task from the neural network application, the library generates a packet that includes the information required for the different stages in the pipeline to perform the tasks. Because the stages correspond to different threads, the library can process multiple packets in parallel which can increase the utilization of the neural network accelerator on the hardware system.

公开(公告)号：US11222256B2

公开(公告)日：2022-01-11

申请号：US15785685

申请日：2017-10-17

Applicant: Xilinx, Inc.

Inventor： Xiao Teng ,  Aaron Ng ,  Ashish Sirasao ,  Elliott Delaye

IPC: G06N3/063 ,  G06N3/08 ,  G06N3/04

Abstract: At least one neural network accelerator performs operations of a first subset of layers of a neural network on an input data set, generates an intermediate data set, and stores the intermediate data set in a shared memory queue in a shared memory. A first processor element of a host computer system provides input data to the neural network accelerator and signals the neural network accelerator to perform the operations of the first subset of layers of the neural network on the input data set. A second processor element of the host computer system reads the intermediate data set from the shared memory queue, performs operations of a second subset of layers of the neural network on the intermediate data set, and generates an output data set while the neural network accelerator is performing the operations of the first subset of layers of the neural network on another input data set.

公开(公告)号：US10678509B1

公开(公告)日：2020-06-09

申请号：US16106743

申请日：2018-08-21

Applicant: Xilinx, Inc.

Inventor： Sean Settle ,  Elliott Delaye ,  Aaron Ng ,  Ehsan Ghasemi ,  Ashish Sirasao ,  Xiao Teng ,  Jindrich Zejda

IPC: G06F7/544 ,  G06F7/533 ,  G06N3/08 ,  G06N3/04

Abstract: An example multiply accumulate (MACC) circuit includes a multiply-accumulator having an accumulator output register, a scaler, coupled to the multiply accumulator, and a control circuit coupled to the multiply-accumulator and the scaler. The control circuit is configured to provide control data to the scaler, the control data indicative of: a most-significant bit (MSB) to least significant bit (LSB) range for selecting bit indices from the accumulator output register for implementing a first right shift; a multiplier; and a second right shift.

公开(公告)号：US11694066B2

公开(公告)日：2023-07-04

申请号：US15785679

申请日：2017-10-17

Applicant: Xilinx, Inc.

Inventor： Aaron Ng ,  Jindrich Zejda ,  Elliott Delaye ,  Xiao Teng ,  Sonal Santan ,  Soren T. Soe ,  Ashish Sirasao ,  Ehsan Ghasemi ,  Sean Settle

IPC: G06N3/063 ,  G06N3/10 ,  G06N3/08 ,  G06N3/04 ,  G06V10/94 ,  G06N3/045

CPC classification number: G06N3/063 ,  G06N3/04 ,  G06N3/08 ,  G06N3/10 ,  G06N3/045 ,  G06V10/955

Abstract: Embodiments herein describe techniques for interfacing a neural network application with a neural network accelerator using a library. The neural network application may execute on a host computing system while the neural network accelerator executes on a massively parallel hardware system, e.g., a FPGA. The library operates a pipeline for submitting the tasks received from the neural network application to the neural network accelerator. In one embodiment, the pipeline includes a pre-processing stage, an FPGA execution stage, and a post-processing stage which each correspond to different threads. When receiving a task from the neural network application, the library generates a packet that includes the information required for the different stages in the pipeline to perform the tasks. Because the stages correspond to different threads, the library can process multiple packets in parallel which can increase the utilization of the neural network accelerator on the hardware system.

公开(公告)号：US10943039B1

公开(公告)日：2021-03-09

申请号：US15786105

申请日：2017-10-17

Applicant: Xilinx, Inc.

Inventor： Ashish Sirasao ,  Elliott Delaye ,  Sean Settle ,  Zhao Ma ,  Ehsan Ghasemi ,  Xiao Teng ,  Aaron Ng ,  Jindrich Zejda

IPC: G06F30/327 ,  G06F7/544 ,  G06N3/04 ,  G06F30/34

Abstract: An example multiply accumulate (MACC) circuit includes: a multiply-accumulator having an accumulator output register; a quantizer, coupled to the multiply accumulator; and a control circuit coupled to the multiply-accumulator and the quantizer, the control circuit configured to provide control data to the quantizer, the control data indicative of a most-significant bit (MSB) to least significant bit (LSB) range for selecting bit indices from the accumulator output register.

公开(公告)号：US20190114535A1

公开(公告)日：2019-04-18

申请号：US15786288

申请日：2017-10-17

Applicant: Xilinx, Inc.

Inventor： Aaron Ng ,  Jindrich Zejda ,  Elliott Delaye ,  Xiao Teng ,  Ashish Sirasao

IPC: G06N3/063 ,  G06N3/04

Abstract: A disclosed neural network processing system includes a host computer system, a RAMs coupled to the host computer system, and neural network accelerators coupled to the RAMs, respectively. The host computer system is configured with software that when executed causes the host computer system to write input data and work requests to the RAMS. Each work request specifies a subset of neural network operations to perform and memory locations in a RAM of the input data and parameters. A graph of dependencies among neural network operations is built and additional dependencies added. The operations are partitioned into coarse grain tasks and fine grain subtasks for optimal scheduling for parallel execution. The subtasks are scheduled to accelerator kernels of matching capabilities. Each neural network accelerator is configured to read a work request from the respective RAM and perform the subset of neural network operations on the input data using the parameters.

公开(公告)号：US20190114529A1

公开(公告)日：2019-04-18

申请号：US15785800

申请日：2017-10-17

Applicant: Xilinx, Inc.

Inventor： Aaron Ng ,  Elliott Delaye ,  Ehsan Ghasemi ,  Xiao Teng ,  Jindrich Zejda ,  Yongjun Wu ,  Sean Settle ,  Ashish Sirasao

IPC: G06N3/04

Abstract: In the disclosed methods and systems for processing in a neural network system, a host computer system writes a plurality of weight matrices associated with a plurality of layers of a neural network to a memory shared with a neural network accelerator. The host computer system further assembles a plurality of per-layer instructions into an instruction package. Each per-layer instruction specifies processing of a respective layer of the plurality of layers of the neural network, and respective offsets of weight matrices in a shared memory. The host computer system writes input data and the instruction package to the shared memory. The neural network accelerator reads the instruction package from the shared memory and processes the plurality of per-layer instructions of the instruction package.

公开(公告)号：US12147379B2

公开(公告)日：2024-11-19

申请号：US18089780

申请日：2022-12-28

Applicant: XILINX, INC.

Inventor： Rajeev Patwari ,  Jorn Tuyls ,  Elliott Delaye ,  Xiao Teng ,  Ephrem Wu

IPC: G06F15/78 ,  G06F13/28

Abstract: Examples herein describe techniques for performing parallel processing using a plurality of processing elements (PEs) and a controller for data that has data dependencies. For example, a calculation may require an entire row or column to be summed, or to determine its mean. The PEs can be assigned different chunks of a data set (e.g., a tensor set, a column, or a row) for processing. The PEs can use one or more tokens to inform the controller when they are done with partial processing of their data chunks. The controller can then gather the partial results and determine an intermediate value for the data set. The controller can then distribute this intermediate value to the PEs which then re-process their respective data chunks using the intermediate value to generate final results.

公开(公告)号：US12079158B2

公开(公告)日：2024-09-03

申请号：US17814817

申请日：2022-07-25

Applicant: Xilinx, Inc.

Inventor： Sanket Pandit ,  Jorn Tuyls ,  Xiao Teng ,  Rajeev Patwari ,  Ehsan Ghasemi ,  Elliott Delaye ,  Aaron Ng

IPC: G06F15/76 ,  G06F9/455 ,  G06F15/80

CPC classification number: G06F15/8053 ,  G06F9/45533

Abstract: An integrated circuit includes a plurality of kernels and a virtual machine coupled to the plurality of kernels. The virtual machine is configured to interpret instructions directed to different ones of the plurality of kernels. The virtual machine is configured to control operation of the different ones of the plurality of kernels responsive to the instructions.

公开(公告)号：US20240045692A1

公开(公告)日：2024-02-08

申请号：US17818309

申请日：2022-08-08

Applicant: Xilinx, Inc.

Inventor： Xiao Teng ,  Tejus Siddagangaiah ,  Bryan Lozano ,  Ehsan Ghasemi ,  Rajeev Patwari ,  Elliott Delaye ,  Jorn Tuyls ,  Aaron Ng ,  Sanket Pandit ,  Pramod Peethambaran ,  Satyaprakash Pareek

IPC: G06F9/38 ,  G06F9/46 ,  G06F9/30

CPC classification number: G06F9/3814 ,  G06F9/467 ,  G06F9/3004

Abstract: Controlling a data processing (DP) array includes creating a replica of a register address space of the DP array based on the design and the DP array. A sequence of instructions, including write instructions and read instructions, is received. The write instructions correspond to buffer descriptors specifying runtime data movements for a design for a DP array. The write instructions are converted into transaction instructions and the read instructions are converted into wait instructions based on the replica of the register address space. The transaction instructions and the wait instructions are included in an instruction buffer. The instruction buffer is provided to a microcontroller configured to execute the transaction instructions and the wait instructions to implement the runtime data movements for the design as implemented in the DP array. In another aspect, the instruction buffer is stored in a file for subsequent execution by the microcontroller.