nvidia-smi command not found on DJI Manifold 2G NVIDIA Jetson TX2

Upon running nvidia-smi through terminal, i am met with nvidia-smi command not found However, i am aware that jetpack 3.3 (the nvidia drivers) have already been installed. Has anyone encountered similar problems with Nvidia jetson tx2 ?

System specs:
DJI Manifold 2G (Nvidia Jetson TX2)
Jetpack 3.3.0
ARMv8 Processor rev 3 (v8l) × 4 ARMv8 Processor rev 0 (v8l) × 2
NVIDIA Tegra X2 (nvgpu)/integrated
8GB ram, Ubuntu 16.04 LTS

UPDATE AND EDIT (SOLVED): While nvidia-smi does not run, One of the answers posted below by user @SeB helped. So after getting the ./deviceQuery executable made, one can see the following. Which tells you the details of your GPU

/usr/local/cuda/samples/1_Utilities/deviceQuery$ ./deviceQuery 
./deviceQuery Starting...

 CUDA Device Query (Runtime API) version (CUDART static linking)

Detected 1 CUDA Capable device(s)

Device 0: "NVIDIA Tegra X2"
  CUDA Driver Version / Runtime Version          9.0 / 9.0
  CUDA Capability Major/Minor version number:    6.2
  Total amount of global memory:                 7839 MBytes (8219348992 bytes)
  ( 2) Multiprocessors, (128) CUDA Cores/MP:     256 CUDA Cores
  GPU Max Clock rate:                            1301 MHz (1.30 GHz)
  Memory Clock rate:                             1600 Mhz
  Memory Bus Width:                              128-bit
  L2 Cache Size:                                 524288 bytes
  Maximum Texture Dimension Size (x,y,z)         1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
  Maximum Layered 1D Texture Size, (num) layers  1D=(32768), 2048 layers
  Maximum Layered 2D Texture Size, (num) layers  2D=(32768, 32768), 2048 layers
  Total amount of constant memory:               65536 bytes
  Total amount of shared memory per block:       49152 bytes
  Total number of registers available per block: 32768
  Warp size:                                     32
  Maximum number of threads per multiprocessor:  2048
  Maximum number of threads per block:           1024
  Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
  Max dimension size of a grid size    (x,y,z): (2147483647, 65535, 65535)
  Maximum memory pitch:                          2147483647 bytes
  Texture alignment:                             512 bytes
  Concurrent copy and kernel execution:          Yes with 1 copy engine(s)
  Run time limit on kernels:                     No
  Integrated GPU sharing Host Memory:            Yes
  Support host page-locked memory mapping:       Yes
  Alignment requirement for Surfaces:            Yes
  Device has ECC support:                        Disabled
  Device supports Unified Addressing (UVA):      Yes
  Supports Cooperative Kernel Launch:            Yes
  Supports MultiDevice Co-op Kernel Launch:      Yes
  Device PCI Domain ID / Bus ID / location ID:   0 / 0 / 0
  Compute Mode:
     < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >

deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 9.0, CUDA Runtime Version = 9.0, NumDevs = 1
Result = PASS

Solution

I think that nvidia-smi is only available so far for NVIDIA discrete GPUs, but Jetsons have an integrated GPU (sharing physical memory with system).

You can find details about your GPU specs with deviceQuery utility in CUDA samples:

cd /usr/local/cuda/samples/1_Utilities//deviceQuery/
sudo make
./deviceQuery

and you may monitor your GPU usage at run-time with tegrastats:

sudo tegrastats

and check for item GR3D such as:

 GR3D_FREQ 0%@318

saying 0% usage with current clock at 318MHz.