To simulate a Network on Chip (NoC) topology in MATLAB has includes to generating a network of processing elements (PEs) or nodes on a chip, in which each node interacts with other nodes using enthusiastic paths or routers. NoCs are usually utilized in multi-core processors to handle data flow among cores proficiently. Typical NoC topologies that contain mesh, torus, tree, and ring.
Here’s a procedure to mimic a simple Mesh NoC topology in MATLAB that is broadly utilized in NoC architectures.
Steps to Simulate a Network on Chip (NoC) Topology
- Define the Mesh Network Structure:
- Organize nodes in a 2D grid in which the each node is associated to its adjacent neighbors like left, right, top, and bottom.
- Describe an adjacency matrix to denote these connections.
- Simulate Data Transmission:
- Enable each node to begin data transmission to any other node in the NoC.
- Execute routing techniques such as XY routing to regulate the shortest path among origin and destination nodes.
- Implement Routing and Transmission Delays:
- Estimate transmission delays according to the distance (hops) among nodes.
- Measure the routing path and latency as data packets transmit via the network.
- Visualize Network Layout and Transmission Activity:
- Measure parameters such as successful transmissions, path taken, and delays.
- Utilize MATLAB plots to envision the mesh layout, routing paths, and data transmission accomplishments.
Example Code for Simulating a Mesh Network on Chip (NoC) Topology
In this instance, we utilize an n×nn \times nn×n mesh topology, and nodes utilize an XY routing techniques to extent their destination.
% Parameters for Mesh NoC Topology Simulation
n = 4; % Dimensions of the NoC (n x n mesh)
numNodes = n * n; % Total number of nodes in the NoC
simulationTime = 30; % Duration of the simulation in seconds
transmissionProbability = 0.2; % Probability of initiating a transmission at each node per time step
distanceBetweenNodes = 1; % Distance between adjacent nodes in arbitrary units
propagationDelay = 1; % Delay per hop in arbitrary units
% Define the 2D grid node positions for visualization
[xPos, yPos] = meshgrid(0:n-1, 0:n-1);
nodePositions = [xPos(:), yPos(:)];
% Define adjacency matrix for mesh topology
adjMatrix = zeros(numNodes);
for i = 1:numNodes
% Find neighbors in the mesh
[x, y] = ind2sub([n, n], i);
if x > 1, adjMatrix(i, sub2ind([n, n], x-1, y)) = 1; end % left
if x < n, adjMatrix(i, sub2ind([n, n], x+1, y)) = 1; end % right
if y > 1, adjMatrix(i, sub2ind([n, n], x, y-1)) = 1; end % bottom
if y < n, adjMatrix(i, sub2ind([n, n], x, y+1)) = 1; end % top
end
% Initialize Transmission Log
transmissions = zeros(numNodes, simulationTime);
% XY Routing Function for NoC
xyRoute = @(src, dst) xyRoutingPath(src, dst, n);
% Simulate Data Transmission in Mesh NoC
for t = 1:simulationTime
for node = 1:numNodes
if rand() < transmissionProbability
% Randomly select a destination node
destNode = randi(numNodes);
if destNode ~= node
% Get the routing path using XY routing
path = xyRoute(node, destNode);
delay = (length(path) – 1) * propagationDelay;
% Log transmissions along the path
for p = 1:length(path)-1
transmissions(path(p), t + p – 1) = 1; % Transmission at each hop
end
disp([‘Time ‘ num2str(t) ‘s: Node ‘ num2str(node) ‘ sent data to Node ‘ num2str(destNode) …
‘ via path [‘ num2str(path) ‘] with delay ‘ num2str(delay) ‘ units’]);
end
end
end
end
% Visualize Mesh NoC Layout
figure;
gplot(adjMatrix, nodePositions, ‘-o’);
title(‘Mesh Network on Chip (NoC) Topology’);
xlabel(‘X Position’);
ylabel(‘Y Position’);
hold on;
text(nodePositions(:, 1), nodePositions(:, 2), arrayfun(@num2str, 1:numNodes, ‘UniformOutput’, false));
hold off;
% Visualize Transmission Activity Over Time
time = 1:simulationTime;
figure;
imagesc(transmissions);
colorbar;
title(‘Transmission Activity Over Time in Mesh NoC’);
xlabel(‘Time (s)’);
ylabel(‘Node ID’);
% XY Routing Helper Function
function path = xyRoutingPath(src, dst, n)
[xSrc, ySrc] = ind2sub([n, n], src);
[xDst, yDst] = ind2sub([n, n], dst);
path = src; % Start at source
% Route in X direction first
while xSrc ~= xDst
xSrc = xSrc + sign(xDst – xSrc);
path = [path, sub2ind([n, n], xSrc, ySrc)];
end
% Route in Y direction
while ySrc ~= yDst
ySrc = ySrc + sign(yDst – ySrc);
path = [path, sub2ind([n, n], xSrc, ySrc)];
end
end
Explanation of the Code
- Parameters:
- n identifies the grid size of the mesh such as a 4×44 \times 44×4 grid outcomes in 16 nodes.
- distanceBetweenNodes and propagationDelay describe the latency per hop among neighboring nodes.
- Mesh Network Structure:
- The adjacency matrix, adjMatrix, denotes connections among each node and its close neighbours in a 2D grid.
- The helper function xyRoutingPath executes XY routing, that routes data horizontally (X-direction) first and then vertically (Y-direction) to extent the destination.
- Transmission Simulation:
- At each time step, every node has a gamble to begin data transmission to a arbitrarily routed destination node.
- If a node starts transmission, the routing path is estimated, and data is routed along the path, with each hop sustaining latency.
- Visualization:
- The first plot demonstrations the physical layout of the NoC mesh topology, shows each node and its connections.
- The second plot demonstrates the transmission activity over time, with each row denotes a node and each column refer as a time step.
Analysis and Extension Ideas
- Variable Propagation Delay: Enable variable propagation latency to replicate differences in link quality among nodes.
- Traffic Patterns: Mimic diverse traffic patterns, like hot-spot traffic in which the particular nodes gets more traffic or multicast/broadcast traffic.
- Fault Tolerance and Rerouting: Execute fault-tolerant mechanisms to reroute nearby failed nodes or links.
- Prioritized Traffic: Execute traffic selection to replicate mixed-criticality workloads, supportive for real-time applications on a NoC.
- Alternative Topologies: Expand the configuration to replicate torus or hierarchical topologies that are also usual in NoC designs.
In this manual, we have delivered the typical procedure that is vital to know when implementing Network on Chip (NoC) topology in MATLAB environment. We also provide samples for your references. If needed, we will guide you through another procedure for you.
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