cuda

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:

1. cuda_demo - runs in-orbit on the SABERTOOTH to demonstrate CUDA running
2. 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:

1. deviceQuery
2. bandwidthTest
3. transpose

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`](https://github.com/nsat/space-services-user-guide/blob/main/tutorials/cuda/deploy). The script uploads `cuda_demo` and schedules it's execution in 24 hours. Replace [YOUR_AUTH_TOKEN] & [YOUR_SAT_ID] as needed. ``` $ ./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](../hello_world/#review)). ## Next Steps - [SABERTOOTH cuDNN Tutorial](../cudnn/)