Design space exploration of correlation computation implementation on FPGA.
Project branch structure
- main - it contains stable project versions
- dev_"shortcut_name" - it contains developers branch; it does not have to be stable; only its stable versions merge with main branch
- Vitis 2022.1
- Vivado 2022.1
- https://github.com/fpgasystems/Coyote/tree/e34ce174415732ea43267de51369d28978624c43 -New flow for Coyote and correlation integration to be released by the end of October
├── baselines
│ └── gpu (compute PCC using PyTorch)
│ └── cpp (sufficient statistics are gathered by the CPU from data stored in the memory)
│ └── outer_lib (extracting the sufficient statistics from the Eigen matrix-matrix multiplication and computing the PCC)
│ └── python (compute PCC using python's pandas or numpy build in functions)
├── coyote_integration
│ └── hdl (RTL *.sv to integrate AMNES as a co-processor kernel into coyote)
│ └── hdl_rdma (RTL *.sv to integrate AMNES as a network attached kernel into coyote)
│ └── host (host CPU *.cpp code)
│ └── host_rdma (remote and host CPU *.cpp code)
│ └── testbench (RTL *.sv to test the RTL compiled from Vitis HLS)
├── hls
│ └── class_method (high level synthesis code for Pearson Correlation Coefficient)
├── bitstreams (progammable FPGA files)
└── co-processor (PCIe data source)
└── rdma (RDMA network stack data source)