Xilinx, Inc.

Hewlett-packard Development Company, L.P.

Hewlett-packard Company

Shail Aditya Gupta

Vinod Kumar Kathail

Michael S Schlansker

B Ramakrishna Rau

Mukund Sivaraman

Samuel R Bayliss

Ralph D Wittig

Philip Bryn James-Roxby

Akella Sastry

Robert S Schreiber

Rishi Surendran

Chia-Jui Hsu

Vidhumouli Hunsigida

L James Hwang

Santosh Abraham

Siddharth Rele

Dinesh K Monga

Kaushik Barman

Bantwal R Rau

Pradip Jha

Vishal Suthar

Abnikant Singh

Scott A Mahlke

Srinivas Beeravolu

Richard C Johnson

Ajit K Agarwal

Siddarth Rele

Prashant S Rawat

Anita B Rau

Darren C Conquist

Sadun Anik

Greg Snider

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

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

Implementing an application using a plurality of data processing engines (DPEs) can include, in a first pass, mapping, using computer hardware, a data flow graph onto an array of DPEs by minimizing direct memory access (DMA) circuit usage and memory conflicts in the array of DPEs and, in response to determining that a mapping solution generated by the first pass requires an additional DMA circuit not specified by the data flow graph, inserting, using the computer hardware, additional buffers into the data flow graph. In a second pass, the additional buffers can be mapped, using the computer hardware, onto the array of DPEs by minimizing the memory conflicts in the array of DPEs.

Implementing an application specified as a data flow graph in an array of data processing engines

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.

Dataflow graph programming environment for a heterogenous processing system

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.

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.

Constraints for applications in a heterogeneous programming environment

For an application having a software portion for implementation in a data processing engine (DPE) array of a device and a hardware portion for implementation in programmable logic (PL) of the device, an implementation flow is performed, using a processor executing a hardware compiler, on the hardware portion based on an interface block solution that maps logical resources used by the software portion to hardware of an interface block coupling the DPE array to the PL. In response to not meeting a design metric during the implementation flow, an interface block constraint is provided from the hardware compiler to a DPE compiler. In response to receiving the interface block constraint, an updated interface block solution is generated, using the processor executing the DPE compiler, and provided from the DPE compiler to the hardware compiler.

Flow convergence during hardware-software design for heterogeneous and programmable devices

For an application specifying a software portion for implementation within a data processing engine (DPE) array of a device and a hardware portion for implementation within programmable logic (PL) of the device, a logical architecture for the application and a first interface solution specifying a mapping of logical resources to hardware of an interface circuit block between the DPE array and the programmable logic are generated. A block diagram of the hardware portion is built based on the logical architecture and the first interface solution. An implementation flow is performed on the block diagram. The software portion of the application is compiled for implementation in one or more DPEs of the DPE array.

Hardware-software design flow for heterogeneous and programmable devices

An example method of placing kernels of an application in a data processing engine array (DPE) of a system on chip (SOC) includes obtaining a graph of the application having nodes representing the kernels and edges representing communication between the kernels, sorting the kernels based on runtime ratio associated with each of the kernels, processing the sorted kernels sequentially to place into partitions, determining an execution order of kernels in each of the partitions; and generating implementation data for the SOC for implementing the application therein based on the determined partitions and execution order for each of the partitions.

Partitioning in a compiler flow for a heterogeneous multi-core architecture

An example method of implementing an application for a system-on-chip (SOC) having a data processing engine (DPE) array includes determining a graph representation of the application, the graph representation including nodes representing kernels of the application and edges representing communication between the kernels, mapping, based on the graph, the kernels onto DPEs of the DPE array and data structures of the kernels onto memory in the DPE array, routing communication channels between DPEs and circuitry of the application configured in programmable logic of the SOC, and generating implementation data for programming the SOC to implement the application based on results of the mapping and the routing.

Compilation flow for a heterogeneous multi-core architecture

An example method of implementing an application for a system-on-chip (SOC) having a data processing engine (DPE) array includes obtaining a graph representation of the application, the graph representation including nodes representing kernels of the application and edges representing communication between the kernels, mapping, based on the graph, the kernels onto DPEs of the DPE array and data structures of the kernels onto memory in the DPE array, routing communication channels between DPEs and circuitry of the application configured in programmable logic of the SOC, adding at least one first-in-first-out (FIFO) buffer to at least one of the communication channels, and generating implementation data for programming the SOC to implement the application based on results of the mapping and the routing.

Stream FIFO insertion in a compilation flow for a heterogeneous multi-core architecture

An embodiment of the present invention includes a pipeline comprising a plurality of stages and a pipeline timing controller controlling a plurality of predetermined delays, wherein, when one of the predetermined delays has expired, the pipeline timing controller sends a control signal to initiate at least one process within associated ones of the plurality of stages.

Pipeline stage initialization via task frame accessed by a memory pointer propagated among the pipeline stages

A method of designing a pipeline comprises the steps of: accepting a task procedure expressed in a standard programming language, the task procedure including a sequence of computational steps; accepting a performance requirement of the pipeline; and automatically creating a hardware description of the pipeline, the pipeline comprising a plurality of interconnected processor stages, each of the processor stages for performing a respective one of the computational steps, the pipeline having characteristics consistent with the performance requirement of the pipeline.

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San Jose, CA, United States of America

Shail Aditya Gupta