Abstract: In some aspects, finer grained parallelism is achieved by segmenting programmatic workloads into smaller discretized portions, where a first element can be indicative both of a configuration or program to be executed, and a first data set to be used in such execution, while a second element can be indicative of a second data element or group. The discretized portions can cause program execute on distributed processors. Approaches to selecting processors, and allocating local memory associated with those processors are disclosed. In one example, discretized portions that share a program have an anti-affinity to cause dispersion, for initial execution assignment. Flags, such as programmer and compiler generated flags can be used in determining such allocations. Workloads can be grouped according to compatibility of memory usage requirements.

Abstract: Aspects comprise systems implementing 3-D graphics processing functionality in a multiprocessing system. Control flow structures are used in scheduling instances of computation in the multiprocessing system, where different points in the control flow structure serve as points where deferral of some instances of computation can be performed in favor of scheduling other instances of computation. In some examples, the control flow structure identifies particular tasks, such as intersection testing of a particular portion of an acceleration structure, and a particular element of shading code. In some examples, the aspects are used in 3-D graphics processing systems that can perform ray tracing based rendering.

Abstract: In some aspects, finer grained parallelism is achieved by segmenting programmatic workloads into smaller discretized portions, where a first element can be indicative both of a configuration or program to be executed, and a first data set to be used in such execution, while a second element can be indicative of a second data element or group. The discretized portions can cause program execute on distributed processors. Approaches to selecting processors, and allocating local memory associated with those processors are disclosed. In one example, discretized portions that share a program have an anti-affinity to cause dispersion, for initial execution assignment. Flags, such as programmer and compiler generated flags can be used in determining such allocations. Workloads can be grouped according to compatibility of memory usage requirements.

Abstract: Aspects include, for example, a method for interpreting information in a computer program, or profiling such a program to estimate a group size for instances of that program (program module, or portion thereof). Such a method can be used in a system that supports collecting outputs of executing instances, where those outputs can specify new program instances. Scheduling of new instances (or allocation of resources for executing such instances) can be deferred. A trigger to begin scheduling (or allocation) for a collection of instances uses a target group size for that program. Thus, different programs can have different group sizes, which can be set explicitly, or based on profiling. The profiling can occur during one or more of pre-execution and during execution. The group size estimate can be an input into an algorithm that also accounts for system state during execution.