Abstract: A parallel processing unit (PPU) can be divided into partitions. Each partition is configured to operate similarly to how the entire PPU operates. A given partition includes a subset of the computational and memory resources associated with the entire PPU. Software that executes on a CPU partitions the PPU for an admin user. A guest user is assigned to a partition and can perform processing tasks within that partition in isolation from any other guest users assigned to any other partitions. Because the PPU can be divided into isolated partitions, multiple CPU processes can efficiently utilize PPU resources.

Abstract: A parallel processing unit (PPU) can be divided into partitions. Each partition is configured to operate similarly to how the entire PPU operates. A given partition includes a subset of the computational and memory resources associated with the entire PPU. Software that executes on a CPU partitions the PPU for an admin user. A guest user is assigned to a partition and can perform processing tasks within that partition in isolation from any other guest users assigned to any other partitions. Because the PPU can be divided into isolated partitions, multiple CPU processes can efficiently utilize PPU resources.

Abstract: A parallel processing unit (PPU) can be divided into partitions. Each partition is configured to operate similarly to how the entire PPU operates. A given partition includes a subset of the computational and memory resources associated with the entire PPU. Software that executes on a CPU partitions the PPU for an admin user. A guest user is assigned to a partition and can perform processing tasks within that partition in isolation from any other guest users assigned to any other partitions. Because the PPU can be divided into isolated partitions, multiple CPU processes can efficiently utilize PPU resources.

Abstract: A parallel processing unit (PPU) can be divided into partitions. Each partition is configured to operate similarly to how the entire PPU operates. A given partition includes a subset of the computational and memory resources associated with the entire PPU. Software that executes on a CPU partitions the PPU for an admin user. A guest user is assigned to a partition and can perform processing tasks within that partition in isolation from any other guest users assigned to any other partitions. Because the PPU can be divided into isolated partitions, multiple CPU processes can efficiently utilize PPU resources.

Abstract: A parallel processing unit (PPU) can be divided into partitions. Each partition is configured to operate similarly to how the entire PPU operates. A given partition includes a subset of the computational and memory resources associated with the entire PPU. Software that executes on a CPU partitions the PPU for an admin user. A guest user is assigned to a partition and can perform processing tasks within that partition in isolation from any other guest users assigned to any other partitions. Because the PPU can be divided into isolated partitions, multiple CPU processes can efficiently utilize PPU resources.

Abstract: A parallel processing unit (PPU), operating in a traditional processing environment or in a virtualized processing environment, can be divided into partitions. Each partition is configured to operate similarly to how the entire PPU operates. A given partition includes a subset of the computational and memory resources associated with the entire PPU. Software that executes on a CPU partitions the PPU for an admin user. A guest user is assigned to a partition and can perform processing tasks within that partition in isolation from any other guest users assigned to any other partitions. Because the PPU can be divided into isolated partitions, multiple CPU processes can efficiently utilize PPU resources.

Abstract: A parallel processing unit (PPU) can be divided into partitions. Each partition is configured to operate similarly to how the entire PPU operates. A given partition includes a subset of the computational and memory resources associated with the entire PPU. Software that executes on a CPU partitions the PPU for an admin user. A guest user is assigned to a partition and can perform processing tasks within that partition in isolation from any other guest users assigned to any other partitions. Because the PPU can be divided into isolated partitions, multiple CPU processes can efficiently utilize PPU resources.

Abstract: A parallel processing unit (PPU) can be divided into partitions. Each partition is configured to operate similarly to how the entire PPU operates. A given partition includes a subset of the computational and memory resources associated with the entire PPU. Software that executes on a CPU partitions the PPU for an admin user. A guest user is assigned to a partition and can perform processing tasks within that partition in isolation from any other guest users assigned to any other partitions. Because the PPU can be divided into isolated partitions, multiple CPU processes can efficiently utilize PPU resources.

Abstract: A parallel processing unit (PPU) can be divided into partitions. Each partition is configured to operate similarly to how the entire PPU operates. A given partition includes a subset of the computational and memory resources associated with the entire PPU. Software that executes on a CPU partitions the PPU for an admin user. A guest user is assigned to a partition and can perform processing tasks within that partition in isolation from any other guest users assigned to any other partitions. Because the PPU can be divided into isolated partitions, multiple CPU processes can efficiently utilize PPU resources.

Abstract: A parallel processing unit (PPU) can be divided into partitions. Each partition is configured to operate similarly to how the entire PPU operates. A given partition includes a subset of the computational and memory resources associated with the entire PPU. Software that executes on a CPU partitions the PPU for an admin user. A guest user is assigned to a partition and can perform processing tasks within that partition in isolation from any other guest users assigned to any other partitions. Because the PPU can be divided into isolated partitions, multiple CPU processes can efficiently utilize PPU resources.

Abstract: One embodiment of the present invention sets forth a technique for executing a software method within a graphics processing unit (GPU) that minimizes the number of clock cycles during which the graphics engine is idled. The function of the software method is performed by a firmware method that is executed by a processor within the GPU. The firmware method is executed to access and optionally update the state stored in the GPU. Unlike execution of a conventional software method, execution of the firmware method does not require an exchange of information between a CPU and the GPU. Therefore, the CPU is not interrupted and throughput of the CPU is not reduced.

Abstract: One embodiment of the present invention sets forth a technique for mid-primitive execution preemption. When preemption is initiated no new instructions are issued, in-flight instructions progress to an execution unit boundary, and the execution state is unloaded from the processing pipeline. The execution units within the processing pipeline, including the coarse rasterization unit complete execution of in-flight instructions and become idle. However, rasterization of a triangle may be preempted at a coarse raster region boundary. The amount of context state to be stored is reduced because the execution units are idle. Preempting at the mid-primitive level during rasterization reduces the time from when preemption is initiated to when another process can execute because the entire triangle is not rasterized.

Abstract: One embodiment of the present invention sets forth a technique for tracking and filtering state change methods provided to a graphics pipeline. State shadow circuitry at the start of the graphics pipeline may be configured in different modes. A track mode is used to capture the current state by storing state change methods that are transmitted to the graphics pipeline. A passthrough mode is used to provide different state data to the graphics pipeline without updating the current state stored in the state shadow circuitry. A replay mode is used to restore the current state to the graphics pipeline using the state shadow circuitry. Additionally, the state shadow circuitry may also be configured to filter the state change methods that are transmitted to graphics pipeline by removing redundant state change methods.

Abstract: One embodiment of the present invention sets forth a method for generating work to be processed by a graphics pipeline residing within a graphics processor. The method includes the steps of receiving an indication that a first graphics workload is to be submitted to a command queue associated with the graphics processor, allocating a first portion of shader accessible memory for one or more units of state information that are necessary for processing the first graphics workload, populating the first portion of shader accessible memory with the one or more units of state information, and transmitting to the command queue of the graphics processor the one or more units of state information stored within the first portion of shader accessible memory, wherein the first graphics workload is processed within the graphics pipeline based on the one or more units of state information.

Abstract: One embodiment of the present invention sets forth a technique for mid-primitive execution preemption. When preemption is initiated no new instructions are issued, in-flight instructions progress to an execution unit boundary, and the execution state is unloaded from the processing pipeline. The execution units within the processing pipeline, including the coarse rasterization unit complete execution of in-flight instructions and become idle. However, rasterization of a triangle may be preempted at a coarse raster region boundary. The amount of context state to be stored is reduced because the execution units are idle. Preempting at the mid-primitive level during rasterization reduces the time from when preemption is initiated to when another process can execute because the entire triangle is not rasterized.

Abstract: One embodiment of the present invention sets forth a method macro expander (MME) coupled to a driver and the processing pipeline of a graphics processing unit. In operation, the MME receives, from the driver, a first packet of work indicating a macro stored in an instruction memory that is to be executed. The MME then executes the commands of the macro in the instruction memory to generate a second packet of work, and the second packet of work is then transmitted to the processing pipeline for further execution.

Abstract: One embodiment of the present invention sets forth a technique instruction level and compute thread array granularity execution preemption. Preempting at the instruction level does not require any draining of the processing pipeline. No new instructions are issued and the context state is unloaded from the processing pipeline. When preemption is performed at a compute thread array boundary, the amount of context state to be stored is reduced because execution units within the processing pipeline complete execution of in-flight instructions and become idle. If, the amount of time needed to complete execution of the in-flight instructions exceeds a threshold, then the preemption may dynamically change to be performed at the instruction level instead of at compute thread array granularity.

Abstract: One embodiment of the present invention sets forth a technique instruction level and compute thread array granularity execution preemption. Preempting at the instruction level does not require any draining of the processing pipeline. No new instructions are issued and the context state is unloaded from the processing pipeline. When preemption is performed at a compute thread array boundary, the amount of context state to be stored is reduced because execution units within the processing pipeline complete execution of in-flight instructions and become idle. If, the amount of time needed to complete execution of the in-flight instructions exceeds a threshold, then the preemption may dynamically change to be performed at the instruction level instead of at compute thread array granularity.

Abstract: One embodiment of the present invention sets forth a [TODO once claims are reviewed]

Abstract: One embodiment of the present invention sets forth a method for generating work to be processed by a graphics pipeline residing within a graphics processor. The method includes the steps of receiving an indication that a first graphics workload is to be submitted to a command queue associated with the graphics processor, allocating a first portion of shader accessible memory for one or more units of state information that are necessary for processing the first graphics workload, populating the first portion of shader accessible memory with the one or more units of state information, and transmitting to the command queue of the graphics processor the one or more units of state information stored within the first portion of shader accessible memory, wherein the first graphics workload is processed within the graphics pipeline based on the one or more units of state information.