Abstract: A method for managing position independent code using a software framework is presented. A software framework provides the ability to cache multiple plug-in's which are loaded in a processor's local storage. A processor receives a command or data stream from another processor, which includes information corresponding to a particular plug-in. The processor uses the plug-in identifier to load the plug-in from shared memory into local memory before it is required in order to minimize latency. When the data stream requests the processor to use the plug-in, the processor retrieves a location offset corresponding to the plug-in and applies the plug-in to the data stream. A plug-in manager manages an entry point table that identifies memory locations corresponding to each plug-in and, therefore, plug-ins may be placed anywhere in a processor's local memory.

Abstract: A computer implemented method and system for the generation of software thermal profiles for applications executed on a set of processors in a simulated environment. Execution of a software program being run on a software simulator is detected and hardware operations for the software program being executed by the set of processors are analyzed to create analyzed information. Then, a thermal index is generated based on the analyzed information.

Abstract: Processor resources are partitioned based on memory usage. A compiler determines the extent to which a process is memory-bound and accordingly divides the process into a number of threads. When a first thread encounters a prolonged instruction, the compiler inserts a conditional branch to a second thread. When the second thread encounters a prolonged instruction, a conditional branch to a third thread is executed. This continues until the last thread conditionally branches back to the first thread. An indirect segmented register file is used so that the “return to” and “branch to” logical registers within each thread are the same (e.g., R1 and R2)for each thread. These logical registers are mapped to hardware registers that store actual addresses. The indirect mapping is altered to bypass completed threads. When the last thread completes it may signal an external process.

Abstract: A method is provided to allow virtual devices that use a plurality of processors in a multiprocessor systems, such as the BE environment. Using this method, a synergistic processing unit (SPU) can either be dedicated to performing a particular function (i.e., audio, video, etc.) or a single SPU can be programmed to perform several functions on behalf of the other processors in the system. The application, preferably running in one of the primary (PU) processors, issues IOCTL commands through device drivers that correspond to SPUs. The kernel managing the primary processors responds by sending an appropriate message to the SPU that is performing the dedicated function. Using this method, an SPU can be virtualized for swapping multiple tasks or dedicated to performing a particular task.

Abstract: A computer implemented method, data processing system, and computer usable code are provided for analytical generation of software thermal profiles. In order to generate a thermal profile, a set of instruction streams are analyzed for a program being executed by a set of processors to create analyzed information. A thermal index is generated based on the analyzed information.

Abstract: A task queue manager manages the task queues corresponding to virtual devices. When a virtual device function is requested, the task queue manager determines whether an SPU is currently assigned to the virtual device task. If an SPU is already assigned, the request is queued in a task queue being read by the SPU. If an SPU has not been assigned, the task queue manager assigns one of the SPUs to the task queue. The queue manager assigns the task based upon which SPU is least busy as well as whether one of the SPUs recently performed the virtual device function. If an SPU recently performed the virtual device function, it is more likely that the code used to perform the function is still in the SPU's local memory and will not have to be retrieved from shared common memory using DMA operations.

Abstract: A computer system's multiple processors are managed as devices. The operating system accesses the multiple processors using processor device modules loaded into the operating system to facilitate a communication between an application requesting access to a processor and the processor. A device-like access is determined for accessing each one of the processors similar to device-like access for other devices in the system such as disk drives, printers, etc. An application seeking access to a processor issues device-oriented instructions for processing data, and in addition, the application provides the processor with the data to be processed. The processor processes the data according to the instructions provided by the application.

Abstract: Code handling, such as interpreting language instructions or performing “just-in-time” compilation, is performed using a heterogeneous processing environment that shares a common memory. In a heterogeneous processing environment that includes a plurality of processors, one of the processors is programmed to perform a dedicated code-handling task, such as perform just-in-time compilation or interpretation of interpreted language instructions, such as Java. The other processors request code handling processing that is performed by the dedicated processor. Speed is achieved using a shared memory map so that the dedicated processor can quickly retrieve data provided by one of the other processors.

Abstract: Computational load is balanced across a plurality of processors. Source code subtasks are compiled into byte code subtasks whereby the byte code subtasks are translated into processor-specific object code subtasks at runtime. The processor-type selection is based upon one of three approaches which are 1) a brute force approach, 2) higher-level approach, or 3) processor availability approach. Each object code subtask is loaded in a corresponding processor type for execution. In one embodiment, a compiler stores a pointer in a byte code file that references the location of a byte code subtask. In this embodiment, the byte code subtask is stored in a shared library and, at runtime, a runtime loader uses the pointer to identify the location of the byte code subtask in order to translate the byte code subtask.

Abstract: Source code subtasks are compiled into byte code subtasks whereby the byte code subtasks are translated into processor-specific object code subtasks at runtime. The processor-type selection is based upon one of three approaches which are 1) a brute force approach, 2) higher-level approach, or 3) processor availability approach. Each object code subtask is loaded in a corresponding processor type for execution. In one embodiment, a compiler stores a pointer in a byte code file that references the location of a byte code subtask. In this embodiment, the byte code subtask is stored in a shared library and, at runtime, a runtime loader uses the pointer to identify the location of the byte code subtask in order to translate the byte code subtask.

Abstract: Asynchronously traversing a disjoint linked data structure is presented. A synergistic processing unit (SPU) includes a handler that works in conjunction with a memory flow controller (MFC) to traverse a disjoint linked data structure. The handler compares a search value with a node value, and provides the MFC with an effective address of the next node to traverse based upon the comparison. In turn, the MFC retrieves the corresponding node data from system memory and stores the node data in the SPU's local storage area. The MFC stalls processing and sends an asynchronous event interrupt to the SPU which, as a result, instructs the handler to retrieve and compare the latest node data in the local storage area with the search value. The traversal continues until the handler matches the search value with a node value or until the handler determines a failed search.

Abstract: A program is into at least two object files: one object file for each of the supported processor environments. During compilation, code characteristics, such as data locality, computational intensity, and data parallelism, are analyzed and recorded in the object file. During run time, the code characteristics are combined with runtime considerations, such as the current load on the processors and the size of the data being processed, to arrive at an overall value. The overall value is then used to determine which of the processors will be assigned the task. The values are assigned based on the characteristics of the various processors. For example, if one processor is better at handling intensive computations against large streams of data, programs that are highly computationally intensive and process large quantities of data are weighted in favor of that processor. The corresponding object is then loaded and executed on the assigned processor.

Abstract: Loading software on a plurality of processors is presented. A processing unit (PU) retrieves a file from system memory and loads it into its internal memory. The PU extracts a processor type from the file's header which identifies whether the file should execute on the PU or a synergistic processing unit (SPU). If an SPU should execute the file, the PU DMA's the file to the SPU for execution. In one embodiment, the file is a combined file which includes both PU and SPU code. In this embodiment, the PU identifies one or more section headers included in the file which indicates embedded SPU code within the combined file. In this embodiment, the PU extracts the SPU code from the combined file and DMA's the extracted code to an SPU for execution.

Abstract: Asynchronously traversing a disjoint linked data structure is presented. A synergistic processing unit (SPU) includes a handler that works in conjunction with a memory flow controller (MFC) to traverse a disjoint linked data structure. The handler compares a search value with a node value, and provides the MFC with an effective address of the next node to traverse based upon the comparison. In turn, the MFC retrieves the corresponding node data from system memory and stores the node data in the SPU's local storage area. The MFC stalls processing and sends an asynchronous event interrupt to the SPU which, as a result, instructs the handler to retrieve and compare the latest node data in the local storage area with the search value. The traversal continues until the handler matches the search value with a node value or until the handler determines a failed search.

Abstract: A system and method for an efficient implementation of a software-managed cache is presented. When an application thread executes on a simple processor, the application thread uses a conditional data select instruction for eliminating a conditional branch instruction when accessing a software-managed cache. An application thread issues a conditional data select instruction (DMA transfer) after a cache directory lookup, wherein the size of the requested data is dependent upon the outcome of the cache directory lookup. When the cache directory lookup results in a cache hit, the application thread requests a transfer of zero bits of data, which results in a DMA controller (DMAC) performing a no-op instruction. When the cache directory lookup results in a cache miss, the application thread requests a data block transfer the size of a corresponding cache line.

Abstract: A processing unit (PU) retrieves a file from system memory and loads it into its internal memory. The PU extracts a processor type from the file's header which identifies whether the file should execute on the PU or a synergistic processing unit (SPU). If an SPU should execute the file, the PU DMA's the file to the SPU for execution. In one embodiment, the file is a combined file which includes both PU and SPU code. In this embodiment, the PU identifies one or more section headers included in the file which indicates embedded SPU code within the combined file. In this embodiment, the PU extracts the SPU code from the combined file and DMA's the extracted code to an SPU for execution.

Abstract: A computer implemented method, data processing system, and computer usable code are provided for generation of hardware thermal profiles for a set of processors. Sampling is performed of the thermal states of the set of processors during the execution of a set of workloads to create sampled information. The sampled information and thermal characteristics of the set of processors are combined and a thermal index is generated based on the sampled information and characteristics of the set of processors.

Abstract: An approach is provided to allow virtual devices that use a plurality of processors in a multiprocessor systems, such as the BE environment. Using this method, a synergistic processing unit (SPU) can either be dedicated to performing a particular function (i.e., audio, video, etc.) or a single SPU can be programmed to perform several functions on behalf of the other processors in the system. The application, preferably running in one of the primary (PU) processors, issues IOCTL commands through device drivers that correspond to SPUs. The kernel managing the primary processors responds by sending an appropriate message to the SPU that is performing the dedicated function. Using this method, an SPU can be virtualized for swapping multiple tasks or dedicated to performing a particular task.

Abstract: An approach that uses a handler to detect asynchronous lock line reservation lost events, and switching tasks based upon whether a condition is true or a mutex lock is acquired is presented. A synergistic processing unit (SPU) invokes a first thread and, during execution, the first thread requests external data that is shared with other threads or processors in the system. This shared data may be protected with a mutex lock or other shared memory synchronization constructs. When requested data is not available, the SPU switches to a second thread and monitors lock line reservation lost events in order to check when the data is available. When the data is available, the SPU switches back to the first thread and processes the first thread's request.

Abstract: An approach for managing position independent code using a software framework is presented. A software framework provides the ability to cache multiple plug-in's which are loaded in a processor's local storage. A processor receives a command or data stream from another processor, which includes information corresponding to a particular plug-in. The processor uses the plug-in identifier to load the plug-in from shared memory into local memory before it is required in order to minimize latency. When the data stream requests the processor to use the plug-in, the processor retrieves a location offset corresponding to the plug-in and applies the plug-in to the data stream. A plug-in manager manages an entry point table that identifies memory locations corresponding to each plug-in and, therefore, plug-ins may be placed anywhere in a processor's local memory.