Abstract: A sampling module that adjusts the sampling density of a static data set. Two or more rays are cast onto a surface from a single point of origin. The ray or rays intersect the surface at various locations. The distance between the intersection points of each pair of adjacent rays is calculated. This distance is the current sample density. The current sample density is compared to the desired sample density. If the current sample density is not equal to the desired sample density then the sample density of the next casting of rays is adjusted accordingly.

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: An image is generated that includes ray traced pixel data and rasterized pixel data. A synergistic processing unit (SPU) uses a rendering algorithm to generate ray traced data for objects that require high-quality image rendering. The ray traced data is fragmented, whereby each fragment includes a ray traced pixel depth value and a ray traced pixel color value. A rasterizer compares ray traced pixel depth values to corresponding rasterized pixel depth values, and overwrites ray traced pixel data with rasterized pixel data when the corresponding rasterized fragment is “closer” to a viewing point, which results in composite data. A display subsystem uses the resultant composite data to generate an image on a user's display.

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: An image that includes ray traced pixel data and rasterized pixel data is generated. A synergistic processing unit (SPU) uses a rendering algorithm to generate ray traced data for objects that require high-quality image rendering. The ray traced data is fragmented, whereby each fragment includes a ray traced pixel depth value and a ray traced pixel color value. A rasterizer compares ray traced pixel depth values to corresponding rasterized pixel depth values, and overwrites ray traced pixel data with rasterized pixel data when the corresponding rasterized fragment is “closer” to a viewing point, which results in composite data. A display subsystem uses the resultant composite data to generate an image on a user's display.

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 sampling module for adaptively sampling static data sets is provided. Two or more rays are cast onto a surface from a single point of origin. The ray or rays intersect the surface at various locations. The distance between the intersection points of each pair of adjacent rays is calculated. This distance is the current sample density. The current sample density is compared to the desired sample density. If the current sample density is not equal to the desired sample density then the sample density of the next casting of rays is adjusted accordingly.

Abstract: A sampling module is provided. Two or more rays are cast onto a surface from a single point of origin. The ray or rays intersect the surface at various locations. The distance between the intersection points of each pair of adjacent rays is calculated. This distance is the current sample density. The current sample density is compared to the desired sample density. If the current sample density is not equal to the desired sample density then the sample density of the next casting of rays is adjusted accordingly.

Abstract: A system and method for providing a persistent function server is provided. A multi-processor environment uses an interface definition language (idl) file to describe a particular function, such as an “add” function. A compiler uses the idl file to generate source code for use in marshalling and de-marshalling data between a main processor and a support processor. A header file is also created that corresponds to the particular function. The main processor includes parameters in the header file and sends the header file to the support processor. For example, a main processor may include two numbers in an “add” header file and send the “add” header file to a support processor that is responsible for performing math functions. In addition, the persistent function server capability of the support processor is programmable such that the support processor may be assigned to execute unique and complex functions.

Abstract: A method and system for solving a large system of dense linear equations using a system having a processing unit and one or more secondary processing units that can access a common memory for sharing data. A set of coefficients corresponding to a system of linear equations is received, and the coefficients, after being placed in matrix form, are divided into blocks and loaded into the common memory. Each of the processors is programmed to perform matrix operations on individual blocks to solve the linear equations. A table containing a list of the matrix operations is created in the common memory to keep track of the operations that have been performed and the operations that are still pending. SPUs determine whether tasks are pending, access the coefficients by accessing the common memory, perform the required tasks, and store the result back in the common memory for the result to be accessible by the PU and the other SPUs.

Abstract: A sampling module for adaptively sampling static data sets is provided. Two or more rays are cast onto a surface from a single point of origin. The ray or rays intersect the surface at various locations. The distance between the intersection points of each pair of adjacent rays is calculated. This distance is the current sample density. The current sample density is compared to the desired sample density. If the current sample density is not equal to the desired sample density then the sample density of the next casting of rays is adjusted accordingly.

Abstract: An input device is disclosed, one embodiment of which provides position information to an information handling system (IHS). The position information includes both location information and spatial orientation information of the input device in real space. The input device includes a location sensor which determines the absolute location of the input device in x, y and z coordinates. The input device also includes a spatial orientation sensor that determines the spatial orientation of the input device in terms of yaw, pitch and roll. The input device further includes a processor that processes the location information and the spatial orientation information of the input device in real space to determine an image view from the perspective of the input device in virtual space. Movement of the input device in real space by a user causes a corresponding movement of an image view from the perspective of the input device in virtual space.

Abstract: A system and method for generating an image that includes ray traced pixel data and rasterized pixel data is presented. A synergistic processing unit (SPU) uses a rendering algorithm to generate ray traced data for objects that require high-quality image rendering. The ray traced data is fragmented, whereby each fragment includes a ray traced pixel depth value and a ray traced pixel color value. A rasterizer compares ray traced pixel depth values to corresponding rasterized pixel depth values, and overwrites ray traced pixel data with rasterized pixel data when the corresponding rasterized fragment is “closer” to a viewing point, which results in composite data. A display subsystem uses the resultant composite data to generate an image on a user's display.

Abstract: A system and method for providing a persistent function server is provided. A multi-processor environment uses an interface definition language (idl) file to describe a particular function, such as an “add” function. A compiler uses the idl file to generate source code for use in marshalling and de-marshalling data between a main processor and a support processor. A header file is also created that corresponds to the particular function. The main processor includes parameters in the header file and sends the header file to the support processor. For example, a main processor may include two numbers in an “add” header file and send the “add” header file to a support processor that is responsible for performing math functions. In addition, the persistent function server capability of the support processor is programmable such that the support processor may be assigned to execute unique and complex functions.

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 system and method for balancing computational load 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: A method and system for solving a large system of dense linear equations using a system having a processing unit and one or more secondary processing units that can access a common memory for sharing data. A set of coefficients corresponding to a system of linear equations is received, and the coefficients, after being placed in matrix form, are divided into blocks and loaded into the common memory. Each of the processors is programmed to perform matrix operations on individual blocks to solve the linear equations. A table containing a list of the matrix operations is created in the common memory to keep track of the operations that have been performed and the operations that are still pending. SPUs determine whether tasks are pending, access the coefficients by accessing the common memory, perform the required, and store the result back in the common memory for the result to be accessible by the PU and the other SPUs.

Abstract: A system and method for compiling source code for multi-processor environments is presented. Source code is compiled which creates an object file whereby the object file includes multiple object code subtasks. Source code subtasks are compiled into object code subtasks using one of three approaches which are 1) a lowbrow approach, 2) a brute force approach, and 3) a program directive approach. Each object code subtask is formatted to run on a particular processor type with a particular architecture, such as a microprocessor-based architecture or a digital signal processor-based architecture. During runtime, each object code is loaded onto its corresponding processor type for execution.

Abstract: A system and a method for sharing a common system memory by a main processor and a plurality of secondary processors. The sharing of the common system memory enables the sharing of data between the processors. The data are loaded into the common memory by the main processor, which divides the data to be processed into data blocks. The size of the data blocks is equal to the size of the registers of the secondary processors. The main processor identifies an available secondary processor to process the first data block. The secondary processor processes the data block and returns the processed data block to the common system memory. The main processor may continue identifying available secondary processors and requesting the available secondary processors to process data blocks until all the data blocks have been processed.