Abstract:
A smart NIC (Network Interface Card) is provided with features to enable the smart NIC to operate as an in-line NIC between a host's NIC and a network. The smart NIC provides pass-through transmission of network flows for the host. Packets sent to and from the host pass through the smart NIC. As a pass-through point, the smart NIC is able to accelerate the performance of the pass-through network flows by analyzing packets, inserting packets, dropping packets, inserting or recognizing congestion information, and so forth. In addition, the smart NIC provides a lightweight transport protocol (LTP) module that enables it to establish connections with other smart NICs. The LTP connections allow the smart NICs to exchange data without passing network traffic through their respective hosts.
Abstract:
A smart NIC (Network Interface Card) is provided with features to enable the smart NIC to operate as an in-line NIC between a host's NIC and a network. The smart NIC provides pass-through transmission of network flows for the host. Packets sent to and from the host pass through the smart NIC. As a pass-through point, the smart NIC is able to accelerate the performance of the pass-through network flows by analyzing packets, inserting packets, dropping packets, inserting or recognizing congestion information, and so forth. In addition, the smart NIC provides a lightweight transport protocol (LTP) module that enables it to establish connections with other smart NICs. The LTP connections allow the smart NICs to exchange data without passing network traffic through their respective hosts.
Abstract:
A method is provided for processing on an acceleration component a machine learning classification model. The machine learning classification model includes a plurality of decision trees, the decision trees including a first amount of decision tree data. The acceleration component includes an acceleration component die and a memory stack disposed in an integrated circuit package. The memory die includes an acceleration component memory having a second amount of memory less than the first amount of decision tree data. The memory stack includes a memory bandwidth greater than about 50 GB/sec and a power efficiency of greater than about 20 MB/sec/mW. The method includes slicing the model into a plurality of model slices, each of the model slices having a third amount of decision tree data less than or equal to the second amount of memory, storing the plurality of model slices on the memory stack, and for each of the model slices, copying the model slice to the acceleration component memory, and processing the model slice using a set of input data on the acceleration component to produce a slice result.
Abstract:
A smart NIC (Network Interface Card) is provided with features to enable the smart NIC to operate as an in-line NIC between a host's NIC and a network. The smart NIC provides pass-through transmission of network flows for the host. Packets sent to and from the host pass through the smart NIC. As a pass-through point, the smart NIC is able to accelerate the performance of the pass-through network flows by analyzing packets, inserting packets, dropping packets, inserting or recognizing congestion information, and so forth. In addition, the smart NIC provides a lightweight transport protocol (LTP) module that enables it to establish connections with other smart NICs. The LTP connections allow the smart NICs to exchange data without passing network traffic through their respective hosts.
Abstract:
A method is provided for processing on an acceleration component a deep neural network. The method includes configuring the acceleration component to perform forward propagation and backpropagation stages of the deep neural network. The acceleration component includes an acceleration component die and a memory stack disposed in an integrated circuit package. The memory stack has a memory bandwidth greater than about 50 GB/sec and a power efficiency of greater than about 20 MB/sec/mW.
Abstract:
A physical server with an offload card including a SoC (system-on-chip) and a FPGA (field programmable gate array) is disclosed. According to one set of embodiments, the SoC can be configured to offload one or more hypervisor functions from a CPU complex of the server that are suited for execution in software, and the FPGA can be configured to offload one or more hypervisor functions from the CPU complex that are suited for execution in hardware.
Abstract:
A method is provided for processing on an acceleration component a deep neural network. The method includes configuring the acceleration component to perform forward propagation and backpropagation stages of the deep neural network. The acceleration component includes an acceleration component die and a memory stack disposed in an integrated circuit package. The memory stack has a memory bandwidth greater than about 50 GB/sec and a power efficiency of greater than about 20 MB/sec/mW.
Abstract:
A method is provided for processing on an acceleration component a machine learning classification model. The machine learning classification model includes a plurality of decision trees, the decision trees including a first amount of decision tree data. The acceleration component includes an acceleration component die and a memory stack disposed in an integrated circuit package. The memory die includes an acceleration component memory having a second amount of memory less than the first amount of decision tree data. The memory stack includes a memory bandwidth greater than about 50 GB/sec and a power efficiency of greater than about 20 MB/sec/mW. The method includes slicing the model into a plurality of model slices, each of the model slices having a third amount of decision tree data less than or equal to the second amount of memory, storing the plurality of model slices on the memory stack, and for each of the model slices, copying the model slice to the acceleration component memory, and processing the model slice using a set of input data on the acceleration component to produce a slice result.
Abstract:
A smart NIC (Network Interface Card) is provided with features to enable the smart NIC to operate as an in-line NIC between a host's NIC and a network. The smart NIC provides pass-through transmission of network flows for the host. Packets sent to and from the host pass through the smart NIC. As a pass-through point, the smart NIC is able to accelerate the performance of the pass-through network flows by analyzing packets, inserting packets, dropping packets, inserting or recognizing congestion information, and so forth. In addition, the smart NIC provides a lightweight transport protocol (LTP) module that enables it to establish connections with other smart NICs. The LTP connections allow the smart NICs to exchange data without passing network traffic through their respective hosts.
Abstract:
A smart NIC (Network Interface Card) is provided with features to enable the smart NIC to operate as an in-line NIC between a host's NIC and a network. The smart NIC provides pass-through transmission of network flows for the host. Packets sent to and from the host pass through the smart NIC. As a pass-through point, the smart NIC is able to accelerate the performance of the pass-through network flows by analyzing packets, inserting packets, dropping packets, inserting or recognizing congestion information, and so forth. In addition, the smart NIC provides a lightweight transport protocol (LTP) module that enables it to establish connections with other smart NICs. The LTP connections allow the smart NICs to exchange data without passing network traffic through their respective hosts.