Hardware Simulation:
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Model CPUs, GPUs, and memory hierarchies.
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Simulate network topologies (e.g., mesh, torus, fat-tree).
Software Simulation:
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Simulate parallel algorithms (e.g., matrix multiplication, FFT).
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Model communication patterns (e.g., MPI, message-passing).
Performance Metrics:
- Measure execution time, throughput, latency, and scalability.
Visualization:
- Use Julia’s plotting libraries (e.g., Plots.jl) to visualize simulation results.
- Implementation Steps Step 1: Set Up the Framework
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Create a Julia package for the simulator (e.g., HPCSimulator.jl).
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Define data structures for hardware components (e.g., nodes, processors, memory).
Step 2: Simulate Parallelism
- Use Julia’s multi-threading and distributed computing features to simulate parallel execution.
Step 3: Simulate Communication
Use MPI.jl or custom message-passing logic to simulate inter-node communication.
Step 4: Simulate Workloads
Implement common HPC workloads (e.g., linear algebra, PDE solvers).
Step 5: Benchmark and Optimize
Use Julia’s benchmarking tools to optimize the simulator’s performance.
- Extend the Simulator Add support for GPU simulation using CUDA.jl.
Implement network topology modeling using graph libraries like LightGraphs.jl.
Add performance metrics and visualization tools.