Control and reconfiguration of data flow graphs on heterogeneous computing platform

    公开(公告)号:US11687327B2

    公开(公告)日:2023-06-27

    申请号:US17695895

    申请日:2022-03-16

    Applicant: XILINX, INC.

    CPC classification number: G06F8/433 G06F9/54 G06F11/3495 G06F16/9024

    Abstract: Embodiments herein use control application programming interfaces (APIs) to control the execution of a dataflow graph in a heterogeneous processing system. That is, embodiments herein describe a programming model along with associated APIs and methods that can control, interact, and at least partially reconfigure a user application (e.g., the dataflow graph) executing on the heterogeneous processing system through a local executing control program. Using the control APIs, users can manipulate such remotely executing graphs directly as local objects and perform control operations on them (e.g., for loading and initializing the graphs; dynamically adjusting parameters for adaptive control; monitoring application parameters, system states and events; scheduling operations to read and write data across the distributed memory boundary of the platform; controlling the execution life-cycle of a subsystem; and partially reconfiguring the computing resources for a new subsystem).

    Control and reconfiguration of data flow graphs on heterogeneous computing platform

    公开(公告)号:US10802807B1

    公开(公告)日:2020-10-13

    申请号:US16420840

    申请日:2019-05-23

    Applicant: Xilinx, Inc.

    Abstract: Embodiments herein use control application programming interfaces (APIs) to control the execution of a dataflow graph in a heterogeneous processing system. That is, embodiments herein describe a programming model along with associated APIs and methods that can control, interact, and at least partially reconfigure a user application (e.g., the dataflow graph) executing on the heterogeneous processing system through a local executing control program. Using the control APIs, users can manipulate such remotely executing graphs directly as local objects and perform control operations on them (e.g., for loading and initializing the graphs; dynamically adjusting parameters for adaptive control; monitoring application parameters, system states and events; scheduling operations to read and write data across the distributed memory boundary of the platform; controlling the execution life-cycle of a subsystem; and partially reconfiguring the computing resources for a new subsystem).

    Hardware-software design flow with high-level synthesis for heterogeneous and programmable devices

    公开(公告)号:US11645053B2

    公开(公告)日:2023-05-09

    申请号:US17500509

    申请日:2021-10-13

    Applicant: Xilinx, Inc.

    CPC classification number: G06F8/41 G06F8/447 H03K19/17724

    Abstract: Implementing an application within an integrated circuit (IC) having a data processing engine (DPE) array coupled to a Network-on-Chip (NoC) can include determining, using computer hardware, data transfer requirements for a software portion of the application intended to execute on the DPE array by simulating data traffic to the NoC as generated by the software portion, generating, using the computer hardware, a NoC routing solution for data paths of the application implemented by the NoC based, at least in part, on the data transfer requirements for the software portion. The software portion can be compiled for execution by different ones of a plurality of DPEs of the DPE array based, at least in part, on the NoC routing solution. Configuration data can be generated using the computer hardware. The configuration data, when loaded into the IC, configures the NoC to implement the NoC routing solution.

    Hardware-software design flow with high-level synthesis for heterogeneous and programmable devices

    公开(公告)号:US11188312B2

    公开(公告)日:2021-11-30

    申请号:US16421444

    申请日:2019-05-23

    Applicant: Xilinx, Inc.

    Abstract: For an application specifying a software portion for implementation within a data processing engine (DPE) array of a device and a hardware portion having High-Level Synthesis (HLS) kernels for implementation within programmable logic (PL) of the device, a first interface solution is generated that maps logical resources used by the software portion to hardware resources of an interface block coupling the DPE array and the PL. A connection graph specifying connectivity among the HLS kernels and nodes of the software portion to be implemented in the DPE array; and, a block diagram based on the connection graph and the HLS kernels are generated. The block diagram is synthesizable. An implementation flow is performed on the block diagram based on the first interface solution. The software portion of the application is compiled for implementation in one or more DPEs of the DPE array.

    Control and reconfiguration of data flow graphs on heterogeneous computing platform

    公开(公告)号:US11281440B1

    公开(公告)日:2022-03-22

    申请号:US17065433

    申请日:2020-10-07

    Applicant: XILINX, INC.

    Abstract: Embodiments herein use control application programming interfaces (APIs) to control the execution of a dataflow graph in a heterogeneous processing system. That is, embodiments herein describe a programming model along with associated APIs and methods that can control, interact, and at least partially reconfigure a user application (e.g., the dataflow graph) executing on the heterogeneous processing system through a local executing control program. Using the control APIs, users can manipulate such remotely executing graphs directly as local objects and perform control operations on them (e.g., for loading and initializing the graphs; dynamically adjusting parameters for adaptive control; monitoring application parameters, system states and events; scheduling operations to read and write data across the distributed memory boundary of the platform; controlling the execution life-cycle of a subsystem; and partially reconfiguring the computing resources for a new subsystem).

    Constraints for applications in a heterogeneous programming environment

    公开(公告)号:US11113030B1

    公开(公告)日:2021-09-07

    申请号:US16420905

    申请日:2019-05-23

    Applicant: Xilinx, Inc.

    Abstract: Examples herein describe techniques for generating dataflow graphs using source code for defining kernels and communication links between those kernels. In one embodiment, the graph is formed using nodes (e.g., kernels) which are communicatively coupled by edges (e.g., the communication links between the kernels). A compiler converts the source code into a bitstream and/or binary code which configures programmable and non-programmable logic in a heterogeneous processing environment of a SoC to execute the graph. The compiler can also consider user-defined constraints when compiling the source code. The constraints can dictate where the kernels and buffers should be placed in the heterogeneous processing environment, performance requirements, data communication routes through the SoC, type of data path, delays, and the like.

    DATAFLOW GRAPH PROGRAMMING ENVIRONMENT FOR A HETEROGENOUS PROCESSING SYSTEM

    公开(公告)号:US20200371761A1

    公开(公告)日:2020-11-26

    申请号:US16420831

    申请日:2019-05-23

    Applicant: Xilinx, Inc.

    Abstract: Examples herein describe techniques for generating dataflow graphs using source code for defining kernels and communication links between those kernels. In one embodiment, the graph is formed using nodes (e.g., kernels) which are communicatively coupled by edges (e.g., the communication links between the kernels). A compiler converts the source code into a bit stream and/or binary code which configure a heterogeneous processing system of a SoC to execute the graph. The compiler uses the graph expressed in source code to determine where to assign the kernels in the heterogeneous processing system. Further, the compiler can select the specific communication techniques to establish the communication links between the kernels and whether synchronization should be used in a communication link. Thus, the programmer can express the dataflow graph at a high-level (using source code) without understanding about how the operator graph is implemented using the heterogeneous hardware in the SoC.

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