The clock’s for that test I’m curious for are 768MHz, 1GHz, and 1. I feel this should be looked into because AMD added extra cache to RDNA1 and got most of their performance increase with RDNA2 out of it so wondering if something similar can happen with Ampere having that extra cache added onto it here in Orin. Or is it just a limitation of the Process node (Samsung 8nm like Desktop Ampere?) that prevents it from hitting Xaiver-level clocks at the config it is at at 15W (Not saying it’s weaker than 15W Xaiver, but surprised it is seemingly clocked lower by a notable amount if my memory serves me right)Įither way though, my other question is can anyone run something like 3DMark or other standardized benchmarks for the GPU? I am very curious as to what benefits over what should be directly relative to Orin’s 16SM GPU (The RTX 3050 Laptop) the 1.5x increase in L1 Cache and the doubling of L2 Cache per-GPC would result as mentioned in the documentation for Orin’s specifications. On that profile, how many CUDA Cores/SMs are active? As that is a massive drop in clocks across both and at least core count in the case of the CPU.Īre the 2 DLA’s and the PVA drawing back that much power to prevent all CPUs running at 1Ghz and the GPU from even hitting half of its potential clock max? (At whatever CUDA/SM count it’s set to at 15W) He reports back that Orin AGX at 15W drops the CPU down to 4 Cores at 1Ghz and the GPU down to only 420MHz? I tested other multi-threading software including NVIDIA’s cuda samples.Hello, just asking after watching this video from JetsonHacks about Orin AGX and reading some of the replies. Ranks Threads Count (s) total sum % Neighbor search 1 8 5001 20.704 5.176 1.5 On 1 MPI rank, each using 8 OpenMP threads Computing: Num Num Call Wall time Giga-Cycles V&F=Potential and force V=Potential only F=Force only Computing: M-Number M-Flops % Flops Pair Search distance check 16235.718832 146121.469 0.0 ![]() RF=Reaction-Field VdW=Van der Waals QSTab=quadratic-spline table NB=Group-cutoff nonbonded kernels NxN=N-by-N cluster Verlet kernels … M E G A - F L O P S A C C O U N T I N G #0: NVIDIA Xavier, compute cap.: 7.2, ECC: no, stat: compatible L2: 2097152 bytes, linesize 64 bytes, assoc. L1: 65536 bytes, linesize 64 bytes, assoc. Running on 1 node with total 8 cores, 8 logical cores, 1 compatible GPU The avg power consumption was 30w which is over15w, Power rail Watts VDDCPUCV 1.07 VDDGPUSOC 20. ![]() ![]() I’m using nvpmodel 0 which sets power mode to MAXN:Ĭpu0: Online=1 Governor=schedutil MinFreq=1190400 MaxFreq=2265600 CurrentFreq=2265600 IdleStates: C1=0 c6=0Ĭpu1: Online=1 Governor=schedutil MinFreq=1190400 MaxFreq=2265600 CurrentFreq=2265600 IdleStates: C1=0 c6=0Ĭpu2: Online=1 Governor=schedutil MinFreq=1190400 MaxFreq=2265600 CurrentFreq=2265600 IdleStates: C1=0 c6=0Ĭpu3: Online=1 Governor=schedutil MinFreq=1190400 MaxFreq=2265600 CurrentFreq=2265600 IdleStates: C1=0 c6=0Ĭpu4: Online=1 Governor=schedutil MinFreq=1190400 MaxFreq=2265600 CurrentFreq=2265600 IdleStates: C1=0 c6=0Ĭpu5: Online=1 Governor=schedutil MinFreq=1190400 MaxFreq=2265600 CurrentFreq=2265600 IdleStates: C1=0 c6=0Ĭpu6: Online=1 Governor=schedutil MinFreq=1190400 MaxFreq=2265600 CurrentFreq=2265600 IdleStates: C1=0 c6=0Ĭpu7: Online=1 Governor=schedutil MinFreq=1190400 MaxFreq=2265600 CurrentFreq=2265600 IdleStates: C1=0 c6=0 Hello, I tried to benchmark yolov3 network with trtexec tool in 15W mode as GPU as target device I have observed the mean power consumption with the help tegrastats api log during the benchmarking process. Htop shows a similar CPU utilization stats. However, the tegrastats command shows that CPU is at less than 40% utilization: I’m able to run the Lysozyme in Water tutorial without issues. I’m compiling GROMACS with the following cmake parameters:Ĭmake … -DGMX_GPU=on -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-10.0 -DGMX_GPU_DETECTION_DONE=on -DGMX_BUILD_OWN_FFTW=on -DGMX_MPI=on -DBUILD_SHARED_LIBS=off -DCMAKE_C_COMPILER=mpicc -DCMAKE_CXX_COMPILER=mpicxxĭGMX_GPU_DETECTION_DONE is set to workaround a GPU detection issue. I’m using NVIDIA Jetson AGX Xavier: 8-Core ARM v8.2 64-Bit CPU, 512-Core Volta GPU, 32 GB 256-Bit LPDDR4x | 137 GB/s RAM. I need some help regarding GROMACS performance.
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