System and method of compiling a program having a mixture of host code and device code to enable Profile Guided Optimization (PGO) for device code execution. An exemplary integrated compiler can compile source code programmed to be executed by a host processor (e.g., CPU) and a co-processor (e.g., a GPU) concurrently. The compilation can generate an instrumented executable code which includes: profile instrumentation counters for the device functions; and instructions for the host processor to allocate and initialize device memory for the counters and to retrieve collected profile information from the device memory to generate instrumentation output. The output is fed back to the compiler for compiling the source code a second time to generate optimized executable code for the device functions defined in the source code.

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.

System and method of compiling a program having a mixture of host code and device code to enable Profile Guided Optimization (PGO) for device code execution. An exemplary integrated compiler can compile source code programmed to be executed by a host processor (e.g., CPU) and a co-processor (e.g., a GPU) concurrently. The compilation can generate an instrumented executable code which includes: profile instrumentation counters for the device functions; and instructions for the host processor to allocate and initialize device memory for the counters and to retrieve collected profile information from the device memory to generate instrumentation output. The output is fed back to the compiler for compiling the source code a second time to generate optimized executable code for the device functions defined in the source code.

A non-transitory computer readable-medium storing a compiler to cause a computer to perform processing for compiling sequence programs including a declaration of a global variable and generating an execution program to be executed by a PLC. When there is a change in a memory address in the PLC assigned to the global variable between before and after edit of a declaration of the global variable, the compiler gives an execution code to synchronize a first value stored at a memory address assigned to an unedited global variable with a second value stored at a memory address assigned to an edited global variable to an execution program corresponding to the sequence program that references the edited global variable.

Method and apparatus are provided for synchronising execution of a plurality of threads on a multi-threaded processor. A program executed by a thread can have a number of synchronisation points corresponding to points where execution is to be synchronised with another thread. Execution of a thread is paused when it reaches a synchronisation point until at least one other thread with which it is intended to be synchronised reaches a corresponding synchronisation point. Execution is subsequently resumed. A control core maintains status data for threads and can cause a thread that is ready to run to use execution resources that were occupied by a thread that is waiting for a synchronisation event.

A method and an apparatus that execute a parallel computing program in a programming language for a parallel computing architecture are described. The parallel computing program is stored in memory in a system with parallel processors. The parallel computing program is stored in a memory to allocate threads between a host processor and a GPU. The programming language includes an API to allow an application to make calls using the API to allocate execution of the threads between the host processor and the GPU. The programming language includes host function data tokens for host functions performed in the host processor and kernel function data tokens for compute kernel functions performed in one or more compute processors, e.g., GPUs or CPUs, separate from the host processor.

Provided are systems and methods for generating program code for an integrated circuit, where instructions in the code synchronize computation engines that support non-blocking instructions. In various examples, a computing device can receiving an input data set including operations to be performed by an integrated circuit device and dependencies between the operations. The input data set can include a non-blocking instruction, and an operation that requires that the non-blocking instruction be completed. The computing device can generate instructions for performing the operation including a particular instruction to wait for a value to be set in a register of the integrated circuit device. The computing device can further generate program code including the non-blocking instruction and the instructions for performing the operation, wherein the non-blocking instruction is configured to set the value in the register.

A non-transitory computer readable-medium storing a compiler to cause a computer to perform processing for compiling sequence programs including a declaration of a global variable and generating an execution program to be executed by a PLC. When there is a change in a memory address in the PLC assigned to the global variable between before and after edit of a declaration of the global variable, the compiler gives an execution code to synchronize a first value stored at a memory address assigned to an unedited global variable with a second value stored at a memory address assigned to an edited global variable to an execution program corresponding to the sequence program that references the edited global variable.

A method for generating a program to run on multiple tiles. The method comprises: receiving an input graph comprising data nodes, compute vertices and edges; receiving an initial tile-mapping specifying which data nodes and vertices are allocated to which tile; and determining a subgraph of the input graph that meets one or more heuristic rules. The rules comprises: the subgraph comprises at least one data node, the subgraph spans no more than a threshold number of tiles in the initial tile-mapping, and the subgraph comprises at least a minimum number of edges outputting to one or more vertices on one or more other tiles. The method further comprises adapting the initial mapping to migrate the data nodes and any vertices of the determined subgraph to said one or more other tiles.

Compiler-optimized context switching may include receiving an instruction indicating a preferred preemption point comprising an instruction address; storing the preferred preemption point in a data structure; determining, based on the data structure, that the preferred preemption point has been reached by a first thread; determining that preemption of the first thread for a second thread has been requested; and performing a context switch to the second thread.