The AMD Versal™
adaptive
SoC AI Engine multi-threaded simulator (aiesimulator) includes the modeling of the global
memory (DDR memory) and the network on chip (NoC) in addition to the AI Engine array. When the application is compiled
using the simulation target, the AI Engine
multi-threaded simulator can be invoked as follows.
aiesimulator –-pkg-dir=./WorkThis will run the AI Engine simulator in the multi-threaded mode consuming some CPU threads.
Using Threads in the AI Engine Simulation
The calculation for the default number of threads used during AI Engine Simulation is based on the number of CPU cores available on the user machine and the number of active AI Engine core tiles used in the AI Engine Design.
In any multi-threaded process, there is overhead associated with the launching and synchronization of threads. The default threads consumed during AI Engine simulation is the optimal number of threads calculated by the multi-threaded model so that the overall computation on each thread should be substantial when compared to the overhead.
By default, the graph.run() function
with no argument specifies a graph that runs forever. The AI Engine compiler generates code to execute the data flow graph in a
perpetual while loop, thus simulation also runs
perpetually. To create terminating programs for debugging, specify graph.run(<number_of_iterations>) in your graph
code to limit the execution for the specified number of iterations. The specified
number of iterations can be any positive integer value.graph::run(-1) also specifies a graph that runs forever.
The AI Engine simulator command first configures the simulator as specified in the compiler generated Work/config/scsim_config.json file. This includes loading PL IP blocks and their connections, configuring I/O data file drivers, and configuring the NoC and global memory (DDR memory) connections. It then executes the specified PS application and finally exits the simulator.
The AI Engine simulator has an
optional --profile option, which enables
printfs in kernel code to appear on the
console, and also generates profile information. Also, the --dump-vcd <filename> option generates a value change dump
(VCD) for the duration of the simulation. The --simulation-cycle-timeout <number-of-cycles> can be used to
exit the simulation after a given number of clock cycles.
graph.run(), the simulation runs forever. You need to press Ctrl+C twice to exit the simulator.--simulation-cycle-timeout option to stop the simulator on the exact
cycle. The total cycles that appear on the profiling report are same on each
run.<iostream> in the kernel code to
enable printfs. The use of #include <iostream> in the kernel code results
in a compilation error for both the x86 simulator and the aiesimulator simulators. The AI Engine simulator reports Average Throughput of each PLIO at the end of the simulation.
The report is printed on the console and in AIESimulator.log
Enabling core(s) of graph G
Waiting for core(s) of graph G to finish execution ...
core(s) are done executing
Exiting!
Cores are done executing but the simulation will run for some more cycles to allow PLIO to be flushed
Stopping Simulator.
Info: /OSCI/SystemC: Simulation stopped by user.
----------------------------------------------------------------------------------------------
Port Name | Type | Average Throughput
----------------------------------------------------------------------------------------------
Input_0 | IN | 1499.787536 MBps
Input_1 | IN | 1480.061002 MBps
Input_2 | IN | 1500.666709 MBps
Input_3 | IN | 1499.567904 MBps
Output_0 | OUT | 1380.798274 MBps
Output_1 | OUT | 1361.883229 MBps
Output_2 | OUT | 1380.798274 MBps
Output_3 | OUT | 1380.798274 MBps
----------------------------------------------------------------------------------------------
JSON file generated successfully!
IP-INFO: deleting ip PSIP_ps_i24
IP-INFO: deleting packet ip
IP-INFO: deleting packet ip
IP-INFO: deleting packet ip
IP-INFO: deleting packet ip
IP-INFO: deleting packet ip
IP-INFO: deleting packet ip
IP-INFO: deleting packet ip
IP-INFO: deleting packet ip
[INFO] : Simulation Finished, Sim result: 0 Total Simulation time 19696001 ps
AIEMLsim feature license is released.The same report is generated in the summary table of the Analysis View of the AMD Vitis™ Unified IDE.
For designs using External Traffic Generators in AI Engine Simulation, throughput values might not be accurate because external traffic generators are not cycle accurate.
|INFO | in_interpolator | Total number of bytes sent : 2048
|INFO | out_interpolator | Total number of bytes received : 4096
|INFO | in_classifier | Total number of bytes sent : 4096
WARNING::[ XTLM_IPC::006 ] out_interpolator Closing Socket
|INFO | out_classifier | Total number of bytes received : 4096
WARNING::[ XTLM_IPC::006 ] in_interpolator Closing Socket
WARNING::[ XTLM_IPC::006 ] out_classifier Closing Socket
WARNING::[ XTLM_IPC::006 ] in_classifier Closing Socket
Stopping Simulator.
Info: /OSCI/SystemC: Simulation stopped by user.
INFO: The PLIO throughput may not be accurate when an External Traffic Generator is used.
----------------------------------------------------------------------------------------------
Port Name | Type | Average Throughput
----------------------------------------------------------------------------------------------
in_interpolator | IN | 315.640219 MBps
in_classifier | IN | 516.259138 MBps
out_classifier | OUT | 618.282816 MBps
out_interpolator | OUT | 617.686090 MBps
----------------------------------------------------------------------------------------------
JSON file generated successfully!
IP-INFO: deleting ip PSIP_ps_i6
[INFO] : Simulation Finished, Sim result: 0 Total Simulation time 27676 ns
AIEsim feature license is released.The Average Throughput will not be reported if the graph is run
indefinitely (graph.run(-1)). Only if AI Engine simulator is
stopped using --simulation-cycle-timeout=<ns> can you see the Average
Throughput at the end of the simulation.
For designs with stalls or deadlock, the Average Throughput reported is 0.
The Average Throughput report in HW Emulation is found in the
simulate.log file.
Graphs and Sub-Graphs Simulation Runtimes
On an AI Engine design consisting of a larger graph composed of smaller sub-graphs, it is recommended to simulate the individual sub graphs first. Once the sub-graphs are verified and meet requirements in terms of functionality and performance, simulation of the larger graph can be attempted. Typically, depending on the size of the sub graphs, simulation time for the larger graph might take longer.