Pinned Loading

1. Initializing Dask Workers with cyBER... Initializing Dask Workers with cyBERT Model

   1

   from dask_cuda import LocalCUDACluster

   2

   from distributed import Client

   3

   import dask

   4

   5

   def worker_init():

2. Create Streamz Workflow for cyBERT Create Streamz Workflow for cyBERT

   1

   def inference(messages):

   2

       worker = dask.distributed.get_worker()

   3

       df = cudf.DataFrame()

   4

       if type(messages) == str:

   5

           df["stream"] = [messages.decode("utf-8")]

3. Define Streamz Source for cyBERT Define Streamz Source for cyBERT

   1

   from streamz import Stream

   2

   consumer_conf = {

   3

           "bootstrap.servers": "localhost:9092",

   4

           "group.id": "group-1",

   5

           "session.timeout.ms": 60000,

4. rapidsai/clx rapidsai/clx Public archive

   A collection of RAPIDS examples for security analysts, data scientists, and engineers to quickly get started applying RAPIDS and GPU acceleration to real-world cybersecurity use cases.

   Jupyter Notebook 167 68

5. receptive_fields_via_spot_stim receptive_fields_via_spot_stim Public

   MATLAB

6. NESC533 NESC533 Public

   Neural Network Modeling Class

   MATLAB