Abstract: An approach is provided for coalescing network commands in a GPU that implements a SIMT architecture. Compatible next network operations from different threads are coalesced into a single network command packet. This reduces the number of network command packets generated and issued by threads, thereby increasing efficiency, and improving throughput. The approach is applicable to any number of threads and any thread organization methodology, such as wavefronts, warps, etc.

Abstract: An electronic device includes one or more data producing nodes and a data consuming node. Each data producing node separately generates two or more portions of a respective block of data. Upon completing generating each portion of the two or more portions of the respective block of data, each data producing node communicates that portion of the respective block of data to the data consuming node. Upon receiving corresponding portions of the respective blocks of data from each of the one or more data producing nodes, the data consuming node performs operations for a model using the corresponding portions of the respective blocks of data.

Abstract: A framework disclosed herein extends a relaxed, scoped memory model to a system that includes nodes across a commodity network and maintains coherency across the system. A new scope, cluster scope, is defined, that allows for memory accesses at scopes less than cluster scope to operate on locally cached versions of remote data from across the commodity network without having to issue expensive network operations. Cluster scope operations generate network commands that are used to synchronize memory across the commodity network.

Abstract: A framework disclosed herein extends a relaxed, scoped memory model to a system that includes nodes across a commodity network and maintains coherency across the system. A new scope, cluster scope, is defined, that allows for memory accesses at scopes less than cluster scope to operate on locally cached versions of remote data from across the commodity network without having to issue expensive network operations. Cluster scope operations generate network commands that are used to synchronize memory across the commodity network.

Abstract: Systems, apparatuses, and methods for generating network messages on a parallel processor are disclosed. A system includes at least a parallel processor, a general purpose processor, and a network interface unit. The parallel processor includes at least a plurality of compute units, a command processor, and a cache. A thread within a kernel executing on a compute unit of the parallel processor generates a network message and stores the network message and a corresponding indication in the cache. In response to detecting the indication of the network message in the cache, the command processor processes and conveys the network message to the network interface unit without involving the general purpose processor.

Abstract: A method of training a neural network includes, at a local computing node, receiving remote parameters from a set of one or more remote computing nodes, initiating execution of a forward pass in a local neural network in the local computing node to determine a final output based on the remote parameters, initiating execution of a backward pass in the local neural network to determine updated parameters for the local neural network, and prior to completion of the backward pass, transmitting a subset of the updated parameters to the set of remote computing nodes.

Abstract: Systems, apparatuses, and methods for generating network messages on a parallel processor are disclosed. A system includes at least a parallel processor, a general purpose processor, and a network interface unit. The parallel processor includes at least a plurality of compute units, a command processor, and a cache. A thread within a kernel executing on a compute unit of the parallel processor generates a network message and stores the network message and a corresponding indication in the cache. In response to detecting the indication of the network message in the cache, the command processor processes and conveys the network message to the network interface unit without involving the general purpose processor.

Abstract: A framework disclosed herein extends a relaxed, scoped memory model to a system that includes nodes across a commodity network and maintains coherency across the system. A new scope, cluster scope, is defined, that allows for memory accesses at scopes less than cluster scope to operate on locally cached versions of remote data from across the commodity network without having to issue expensive network operations. Cluster scope operations generate network commands that are used to synchronize memory across the commodity network.

Abstract: An approach is provided for coalescing network commands in a GPU that implements a SIMT architecture. Compatible next network operations from different threads are coalesced into a single network command packet. This reduces the number of network command packets generated and issued by threads, thereby increasing efficiency, and improving throughput. The approach is applicable to any number of threads and any thread organization methodology, such as wavefronts, warps, etc.

Abstract: A processing system includes a first processor couplable to a first memory and a second memory. In response to a page migration trigger for a page in the first memory, the first processor is configured to, responsive to the page being a read-only page storing code for execution, initiate migration of the page to a code cache portion of a second memory associated with a second processor and shared by multiple processes executing at the second processor, and to configure each process of a set of processes executing at the second processor to access and execute the code from the code cache portion.

Abstract: A method includes storing a first portion of a sparse triangular matrix in a local memory and launching a kernel for executing a set of workgroups. The first portion includes a plurality of row blocks, and each workgroup in the set of workgroups is associated with one of the plurality of row blocks. The method also includes, for each workgroup in the set of workgroups, solving the row block. The row block is solved by, for each row segment of a first subset of row segments in the row block, calculating a partial sum for the row segment based on one or more matrix elements in the row segment, and writing the partial sum to a remote memory of a first remote processing unit prior to terminating the kernel.

Abstract: Systems, apparatuses, and methods for performing network packet templating for graphics processing unit (GPU)-initiated communication are disclosed. A central processing unit (CPU) creates a network packet according to a template and populates a first subset of fields of the network packet with static data. Next, the CPU stores the network packet in a memory. A GPU initiates execution of a kernel and detects a network communication request within the kernel and prior to the kernel completing execution. Responsive to this determination, the GPU populates a second subset of fields of the network packet with runtime data. Then, the GPU generates a notification that the network packet is ready to be processed. A network interface controller (NIC) processes the network packet using data retrieved from the first subset of fields and from the second subset of fields responsive to detecting the notification.

Abstract: Techniques for improved networking performance in systems where a graphics processing unit or other highly parallel non-central-processing-unit (referred to as an accelerated processing device or “APD” herein) has the ability to directly issue commands to a networking device such as a network interface controller (“NIC”) are disclosed. According to a first technique, the latency associated with loading certain metadata into NIC hardware memory is reduced or eliminated by pre-fetching network command queue metadata into hardware network command queue metadata slots of the NIC, thereby reducing the latency associated with fetching that metadata at a later time. A second technique involves reducing latency by prioritizing work on an APD when it is known that certain network traffic is soon to arrive over the network via a NIC.

Abstract: A method includes storing a first portion of a sparse triangular matrix in a local memory and launching a kernel for executing a set of workgroups. The first portion includes a plurality of row blocks, and each workgroup in the set of workgroups is associated with one of the plurality of row blocks. The method also includes, for each workgroup in the set of workgroups, solving the row block. The row block is solved by, for each row segment of a first subset of row segments in the row block, calculating a partial sum for the row segment based on one or more matrix elements in the row segment, and writing the partial sum to a remote memory of a first remote processing unit prior to terminating the kernel.

Abstract: Systems, apparatuses, and methods for performing network packet templating for graphics processing unit (GPU)-initiated communication are disclosed. A central processing unit (CPU) creates a network packet according to a template and populates a first subset of fields of the network packet with static data. Next, the CPU stores the network packet in a memory. A GPU initiates execution of a kernel and detects a network communication request within the kernel and prior to the kernel completing execution. Responsive to this determination, the GPU populates a second subset of fields of the network packet with runtime data. Then, the GPU generates a notification that the network packet is ready to be processed. A network interface controller (NIC) processes the network packet using data retrieved from the first subset of fields and from the second subset of fields responsive to detecting the notification.

Abstract: A method of training a neural network includes, at a local computing node, receiving remote parameters from a set of one or more remote computing nodes, initiating execution of a forward pass in a local neural network in the local computing node to determine a final output based on the remote parameters, initiating execution of a backward pass in the local neural network to determine updated parameters for the local neural network, and prior to completion of the backward pass, transmitting a subset of the updated parameters to the set of remote computing nodes.

Abstract: Systems, apparatuses, and methods for generating network messages on a parallel processor are disclosed. A system includes at least a parallel processor, a general purpose processor, and a network interface unit. The parallel processor includes at least a plurality of compute units, a command processor, and a cache. A thread within a kernel executing on a compute unit of the parallel processor generates a network message and stores the network message and a corresponding indication in the cache. In response to detecting the indication of the network message in the cache, the command processor processes and conveys the network message to the network interface unit without involving the general purpose processor.