SABERTOOTH CUDA Tutorial

Complexity:	Low
Payloads:	`SABERTOOTH`
Windows:	`PAYLOAD_SABERTOOTH`

This tutorial demonstrates CUDA v10.0 by running the samples that come shipped with NVIDIA CUDA v10.0.

Prerequisites

All tutorials require the steps outlined in the Getting Started Guide.

Overview

The tutorial comes with 2 scripts:

cuda_demo - runs in-orbit on the SABERTOOTH to demonstrate CUDA running
deploy - run by the user on the ground to upload cuda_demo and schedule it to execute in a PAYLOAD_SABERTOOTH window

cuda_demo Script

cuda_demo builds & runs 3 of the CUDA samples:

First, the CUDA compiler is checked for availability:

$ /usr/local/cuda/bin/nvcc -V

Next, the CUDA samples source is copied to ~/ as the system location is not writable:

$ cp -a /usr/local/cuda/samples ~/

Finally some of the CUDA samples are built & run. Here are the commands for building & running deviceQuery:

$ cd ~/samples/1_Utilities/deviceQuery
$ make
$ ./deviceQuery

Example Output

+ cd /home/spire/samples/1_Utilities/deviceQuery
+ make
/usr/local/cuda-10.0/bin/nvcc -ccbin g++ -I../../common/inc  -m64    -gencode arch=compute_30,code=sm_30 -gencode arch=compute_32,code=sm_32 -gencode arch=compute_53,code=sm_53 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_62,code=sm_62 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_72,code=sm_72 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_75,code=compute_75 -o deviceQuery.o -c deviceQuery.cpp
/usr/local/cuda-10.0/bin/nvcc -ccbin g++   -m64      -gencode arch=compute_30,code=sm_30 -gencode arch=compute_32,code=sm_32 -gencode arch=compute_53,code=sm_53 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_62,code=sm_62 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_72,code=sm_72 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_75,code=compute_75 -o deviceQuery deviceQuery.o
mkdir -p ../../bin/aarch64/linux/release
cp deviceQuery ../../bin/aarch64/linux/release
+ ./deviceQuery
./deviceQuery Starting...

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

Detected 1 CUDA Capable device(s)

Device 0: "NVIDIA Tegra X1"
  CUDA Driver Version / Runtime Version          10.0 / 10.0
  CUDA Capability Major/Minor version number:    5.3
  Total amount of global memory:                 1980 MBytes (2076352512 bytes)
  ( 1) Multiprocessors, (128) CUDA Cores/MP:     128 CUDA Cores
  GPU Max Clock rate:                            922 MHz (0.92 GHz)
  Memory Clock rate:                             13 Mhz
  Memory Bus Width:                              64-bit
  L2 Cache Size:                                 262144 bytes
  Maximum Texture Dimension Size (x,y,z)         1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
  Maximum Layered 1D Texture Size, (num) layers  1D=(16384), 2048 layers
  Maximum Layered 2D Texture Size, (num) layers  2D=(16384, 16384), 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:                     Yes
  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
  Device supports Compute Preemption:            No
  Supports Cooperative Kernel Launch:            No
  Supports MultiDevice Co-op Kernel Launch:      No
  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 = 10.0, CUDA Runtime Version = 10.0, NumDevs = 1
Result = PASS

Upload & Deploy

Run deploy. The script uploads cuda_demo and schedules it's execution in 24 hours.

$ ./deploy "[YOUR_AUTH_TOKEN]" [YOUR_SAT_ID]

Review

Once the window has completed and enough time has passed for the log to download, it can be reviewed in AWS S3 (see Hello World tutorial).

Next Steps

SABERTOOTH cuDNN Tutorial