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Communication of USB3.0 Chip with FPGA
Špeťko, Matej ; Viktorin, Jan (referee) ; Košař, Vlastimil (advisor)
SEC6NET is an abbreviation for project Modern tools for detection and mitigation of cyber criminality on the New Generation Internet. Project is focused on research and development of means for monitoring and analysing the network flow. Probes for monitoring IPv6 networks are developed within this project. Probes are using hardware acceleration based on FPGA platform. My thesis connects two technologies: FPGA and USB. The goal is to transfer data from the FPGA microchip to PC using Cypress EZ-USB FX3 microcontroller. The first part is focused on transferring data from FPGA to FX3 microcontroller. Second part describes the modification of FX3 firmware for getting maximum throughput. The last part focuses on implementing PC application for Linux operating system. The application receives data from the probe and saves them into hard drive using PCAP format.
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Efficient Communication in Multi-GPU Systems
Špeťko, Matej ; Jaroš, Jiří (referee) ; Vaverka, Filip (advisor)
After the introduction of CUDA by Nvidia, the GPUs became devices capable of accelerating any general purpose computation. GPUs are designed as parallel processors which posses huge computation power. Modern supercomputers are often equipped with GPU accelerators. Sometimes single GPU performance is not enough for a scientific application and it needs to scale over multiple GPUs. During the computation, there is a need for the GPUs to exchange partial results. This communication represents computation overhead and it is important to research methods of the effective communication between GPUs. This means less CPU involvement, lower latency and shared system buffers. This thesis is focused on inter-node and intra-node GPU-to-GPU communication using GPUDirect technologies from Nvidia and CUDA-Aware MPI. Subsequently, k-Wave toolbox for simulating the propagation of acoustic waves is introduced. This application is accelerated by using CUDA-Aware MPI. Peer-to-peer transfer support is also integrated to k-Wave using CUDA Inter-process Communication.
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Efficient Communication in Multi-GPU Systems
Špeťko, Matej ; Jaroš, Jiří (referee) ; Vaverka, Filip (advisor)
After the introduction of CUDA by Nvidia, the GPUs became devices capable of accelerating any general purpose computation. GPUs are designed as parallel processors which posses huge computation power. Modern supercomputers are often equipped with GPU accelerators. Sometimes the performance or the memory capacity of a single GPU is not enough for a scientific application. The application needs to be scaled into multiple GPUs. During the computation there is need for the GPUs to exchange partial results. This communication represents computation overhead. For this reason it is important to research the methods of the effective communication between GPUs. This means less CPU involvement, lower latency, shared system buffers. Inter-node and intra-node communication is examined. The main focus is on GPUDirect technologies from Nvidia and CUDA-Aware MPI. Subsequently k-Wave toolbox for simulating the propagation of acoustic waves is introduced. This application is accelerated by using CUDA-Aware MPI.
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Efficient Communication in Multi-GPU Systems
Špeťko, Matej ; Jaroš, Jiří (referee) ; Vaverka, Filip (advisor)
After the introduction of CUDA by Nvidia, the GPUs became devices capable of accelerating any general purpose computation. GPUs are designed as parallel processors which posses huge computation power. Modern supercomputers are often equipped with GPU accelerators. Sometimes the performance or the memory capacity of a single GPU is not enough for a scientific application. The application needs to be scaled into multiple GPUs. During the computation there is need for the GPUs to exchange partial results. This communication represents computation overhead. For this reason it is important to research the methods of the effective communication between GPUs. This means less CPU involvement, lower latency, shared system buffers. Inter-node and intra-node communication is examined. The main focus is on GPUDirect technologies from Nvidia and CUDA-Aware MPI. Subsequently k-Wave toolbox for simulating the propagation of acoustic waves is introduced. This application is accelerated by using CUDA-Aware MPI.
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|
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Efficient Communication in Multi-GPU Systems
Špeťko, Matej ; Jaroš, Jiří (referee) ; Vaverka, Filip (advisor)
After the introduction of CUDA by Nvidia, the GPUs became devices capable of accelerating any general purpose computation. GPUs are designed as parallel processors which posses huge computation power. Modern supercomputers are often equipped with GPU accelerators. Sometimes single GPU performance is not enough for a scientific application and it needs to scale over multiple GPUs. During the computation, there is a need for the GPUs to exchange partial results. This communication represents computation overhead and it is important to research methods of the effective communication between GPUs. This means less CPU involvement, lower latency and shared system buffers. This thesis is focused on inter-node and intra-node GPU-to-GPU communication using GPUDirect technologies from Nvidia and CUDA-Aware MPI. Subsequently, k-Wave toolbox for simulating the propagation of acoustic waves is introduced. This application is accelerated by using CUDA-Aware MPI. Peer-to-peer transfer support is also integrated to k-Wave using CUDA Inter-process Communication.
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Communication of USB3.0 Chip with FPGA
Špeťko, Matej ; Viktorin, Jan (referee) ; Košař, Vlastimil (advisor)
SEC6NET is an abbreviation for project Modern tools for detection and mitigation of cyber criminality on the New Generation Internet. Project is focused on research and development of means for monitoring and analysing the network flow. Probes for monitoring IPv6 networks are developed within this project. Probes are using hardware acceleration based on FPGA platform. My thesis connects two technologies: FPGA and USB. The goal is to transfer data from the FPGA microchip to PC using Cypress EZ-USB FX3 microcontroller. The first part is focused on transferring data from FPGA to FX3 microcontroller. Second part describes the modification of FX3 firmware for getting maximum throughput. The last part focuses on implementing PC application for Linux operating system. The application receives data from the probe and saves them into hard drive using PCAP format.
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