Abstract: Methods and systems for optimizing an application for a computing system having multiple distinct memory locations that are interconnected by one or more communication channels include determining one or more data handling properties for a data region in an application. One or more data handling policies for the data region are determined based on the one or more data handling properties. Data setup costs are determined for a scope in the application that uses the data region in different memory locations based on the one or more data handling properties. The application is optimized in accordance with the one or more data handling policies and the data setup costs for the different memory locations.

Abstract: Methods and systems for optimizing an application for a computing system having multiple distinct memory locations that are interconnected by one or more communication channels include determining one or more data handling properties for a data region in an application. One or more data handling policies for the data region are determined based on the one or more data handling properties. Data setup costs are determined for a scope in the application that uses the data region in different memory locations based on the one or more data handling properties. The application is optimized in accordance with the one or more data handling policies and the data setup costs for the different memory locations.

Abstract: An example operation may include one or more of generating a proposal to perform a ledger operation at a first node, informing one or more second nodes of the proposal, receiving a decision on consensus among the first node and the one or more second nodes for the proposal, and performing the ledger operation at the first node when there is consensus, wherein the ledger operation changes a state database of a ledger of the first node and wherein the state database corresponds to a blockchain stored in the ledger.

Abstract: Methods and systems for optimizing an application for a computing system having multiple distinct memory locations that are interconnected by one or more communication channels include determining one or more data handling properties for a data region in an application. One or more data handling policies for the data region are determined based on the one or more data handling properties. Data setup costs are determined for a scope in the application that uses the data region in different memory locations based on the one or more data handling properties. The application is optimized in accordance with the one or more data handling policies and the data setup costs for the different memory locations.

Abstract: Methods and systems for optimizing an application for a computing system having multiple distinct memory locations that are interconnected by one or more communication channels include determining one or more data handling properties for a data region in an application. One or more data handling policies for the data region are determined based on the one or more data handling properties. Data setup costs are determined for a scope in the application that uses the data region in different memory locations based on the one or more data handling properties. The application is optimized in accordance with the one or more data handling policies and the data setup costs for the different memory locations.

Abstract: An example operation may include one or more of generating a proposal to perform a ledger operation at a first node, informing one or more second nodes of the proposal, receiving a decision on consensus among the first node and the one or more second nodes for the proposal, and performing the ledger operation at the first node when there is consensus, wherein the ledger operation changes a state database of a ledger of the first node and wherein the state database corresponds to a blockchain stored in the ledger.

Abstract: Embodiments for construction of a machine learning model for structured inputs by a processor. A domain knowledge may be applied to identify the one or more grammar entities. Input data may be arranged into one or more grammar entities identified using the domain knowledge. Each of the one or more grammar entities may be modularly adapted to one or more grammar entity functions to create a machine learning model. One or more rules may be used to create each of the one or more grammar entity functions.

Abstract: In one embodiment, a computer-implemented method includes receiving source code to be compiled into an executable file for an unaligned instruction set architecture (ISA). Aligned assembled code is generated, by a computer processor. The aligned assembled code complies with an aligned ISA and includes aligned processor code for a processor and aligned accelerator code for an accelerator. A first linking pass is performed on the aligned assembled code, including relocating a first relocation target in the aligned accelerator code that refers to a first object outside the aligned accelerator code. Unaligned assembled code is generated in accordance with the unaligned ISA and includes unaligned accelerator code for the accelerator and unaligned processor code for the processor. A second linking pass is performed on the unaligned assembled code, including relocating a second relocation target outside the unaligned accelerator code that refers to an object in the unaligned accelerator code.

Abstract: According to one embodiment, a method of creating compiler-generated memory mapping hints in a computer system includes analyzing code, by a compiler of the computer system, to identify data access patterns in the code. System configuration information defining data processing system characteristics of a target system for the code is accessed. The data processing system characteristics include a plurality of processing resources and memory domain characteristics relative to the processing resources. A preferred allocation of data in memory domains of the target system is determined based on mapping the code to one or more selected processing resources and mapping the data to one or more of the memory domains based on the memory domain characteristics relative to the one or more selected processing resources. The preferred allocation is stored as compiler-generated memory mapping hints in a format accessible by a physical memory mapping resource of the target system.

Abstract: In one embodiment, a computer-implemented method includes receiving source code to be compiled into an executable file for an unaligned instruction set architecture (ISA). Aligned assembled code is generated, by a computer processor. The aligned assembled code complies with an aligned ISA and includes aligned processor code for a processor and aligned accelerator code for an accelerator. A first linking pass is performed on the aligned assembled code, including relocating a first relocation target in the aligned accelerator code that refers to a first object outside the aligned accelerator code. Unaligned assembled code is generated in accordance with the unaligned ISA and includes unaligned accelerator code for the accelerator and unaligned processor code for the processor. A second linking pass is performed on the unaligned assembled code, including relocating a second relocation target outside the unaligned accelerator code that refers to an object in the unaligned accelerator code.

Abstract: Methods and systems for optimizing an application for a computing system having multiple distinct memory locations that are interconnected by one or more communication channels include determining one or more data handling properties for a data region in an application. One or more data handling policies for the data region are determined based on the one or more data handling properties. Data setup costs are determined for a scope in the application that uses the data region in different memory locations based on the one or more data handling properties. The application is optimized in accordance with the one or more data handling policies and the data setup costs for the different memory locations.

Abstract: In one embodiment, a computer-implemented method includes receiving source code to be compiled into an executable file for an unaligned instruction set architecture (ISA). Aligned assembled code is generated, by a computer processor. The aligned assembled code complies with an aligned ISA and includes aligned processor code for a processor and aligned accelerator code for an accelerator. A first linking pass is performed on the aligned assembled code, including relocating a first relocation target in the aligned accelerator code that refers to a first object outside the aligned accelerator code. Unaligned assembled code is generated in accordance with the unaligned ISA and includes unaligned accelerator code for the accelerator and unaligned processor code for the processor. A second linking pass is performed on the unaligned assembled code, including relocating a second relocation target outside the unaligned accelerator code that refers to an object in the unaligned accelerator code.

Abstract: In one embodiment, a computer-implemented method includes receiving source code to be compiled into an executable file for an unaligned instruction set architecture (ISA). Aligned assembled code is generated, by a computer processor. The aligned assembled code complies with an aligned ISA and includes aligned processor code for a processor and aligned accelerator code for an accelerator. A first linking pass is performed on the aligned assembled code, including relocating a first relocation target in the aligned accelerator code that refers to a first object outside the aligned accelerator code. Unaligned assembled code is generated in accordance with the unaligned ISA and includes unaligned accelerator code for the accelerator and unaligned processor code for the processor. A second linking pass is performed on the unaligned assembled code, including relocating a second relocation target outside the unaligned accelerator code that refers to an object in the unaligned accelerator code.

Abstract: Embodiments relate to program structure-based blocking. An aspect includes receiving source code corresponding to a computer program by a compiler of a computer system. Another aspect includes determining a prefetching section in the source code by a marking module of the compiler. Yet another aspect includes performing, by a blocking module of the compiler, blocking of instructions located in the prefetching section into instruction blocks, such that the instruction blocks of the prefetching section only contain instructions that are located in the prefetching section.

Abstract: Embodiments relate to program structure-based blocking. An aspect includes receiving source code corresponding to a computer program by a compiler of a computer system. Another aspect includes determining a prefetching section in the source code by a marking module of the compiler. Yet another aspect includes performing, by a blocking module of the compiler, blocking of instructions located in the prefetching section into instruction blocks, such that the instruction blocks of the prefetching section only contain instructions that are located in the prefetching section.

Abstract: In one embodiment, a computer-implemented method includes tracking a size of a load-store queue (LSQ) during compile time of a program. The size of the LSQ is time-varying and indicates how many memory access instructions of the program are on the LSQ. The method further includes scheduling, by a computer processor, a plurality of memory access instructions of the program based on the size of the LSQ.

Abstract: In one embodiment, a computer-implemented method includes tracking a size of a load-store queue (LSQ) during compile time of a program. The size of the LSQ is time-varying and indicates how many memory access instructions of the program are on the LSQ. The method further includes scheduling, by a computer processor, a plurality of memory access instructions of the program based on the size of the LSQ.

Abstract: An aspect includes a table of contents (TOC) that was generated by a compiler being received at an accelerator device. The TOC includes an address of global data in a host memory space. The global data is copied from the address in the host memory space to an address in the device memory space. The address in the host memory space is obtained from the received TOC. The received TOC is updated to indicate that global data is stored at the address in the device memory space. A kernel that accesses the global data from the address in the device memory space is executed. The address in the device memory space is obtained based on contents of the updated TOC. When the executing is completed, the global data from the address in the device memory space is copied to the address in the host memory space.

Abstract: An aspect includes a table of contents (TOC) that was generated by a compiler being received at an accelerator device. The TOC includes an address of global data in a host memory space. The global data is copied from the address in the host memory space to an address in the device memory space. The address in the host memory space is obtained from the received TOC. The received TOC is updated to indicate that global data is stored at the address in the device memory space. A kernel that accesses the global data from the address in the device memory space is executed. The address in the device memory space is obtained based on contents of the updated TOC. When the executing is completed, the global data from the address in the device memory space is copied to the address in the host memory space.

Abstract: In one embodiment, a computer-implemented method includes receiving source code to be compiled into an executable file for an unaligned instruction set architecture (ISA). Aligned assembled code is generated, by a computer processor. The aligned assembled code complies with an aligned ISA and includes aligned processor code for a processor and aligned accelerator code for an accelerator. A first linking pass is performed on the aligned assembled code, including relocating a first relocation target in the aligned accelerator code that refers to a first object outside the aligned accelerator code. Unaligned assembled code is generated in accordance with the unaligned ISA and includes unaligned accelerator code for the accelerator and unaligned processor code for the processor. A second linking pass is performed on the unaligned assembled code, including relocating a second relocation target outside the unaligned accelerator code that refers to an object in the unaligned accelerator code.