+-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | 0 N/A N/A 3559 G /usr/lib/xorg/Xorg 95MiB | | 0 N/A N/A 3775 G /usr/bin/gnome-shell 58MiB | +-----------------------------------------------------------------------------------------+ nvidia@localhost:~$ systemctl stop gdm ==== AUTHENTICATING FOR org.freedesktop.systemd1.manage-units ==== Authentication is required to stop 'gdm.service'. Authenticating as: nvidia Password: ==== AUTHENTICATION COMPLETE ==== nvidia@localhost:~$ nvidia-smi -i 0 Fri Jul 24 11:58:10 2026 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 580.00 Driver Version: 580.00 CUDA Version: 13.0 | +-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA Thor Off | 00000000:01:00.0 Off | N/A | | N/A 40C N/A 1W / N/A | Not Supported | 0% Default | | | | Disabled | +-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | No running processes found | +-----------------------------------------------------------------------------------------+ nvidia@localhost:~$ nvidia-smi -L GPU 0: NVIDIA Thor (UUID: GPU-a7c66ad2-6dbb-0ab8-c1a2-37ba6dba3600) nvidia@localhost:~$ nvidia-smi -i 0 -mig 1 Unable to enable MIG Mode for GPU 00000000:01:00.0: Insufficient Permissions Terminating early due to previous errors. nvidia@localhost:~$ sudo nvidia-smi -i 0 -mig 1 Enabled MIG Mode for GPU 00000000:01:00.0
Warning: persistence mode is disabled on device 00000000:01:00.0. See the Known Issues section of the nvidia-smi(1) man page for more information. Run with [--help | -h] switch to get more information on how to enable persistence mode. All done. nvidia@localhost:~$ nvidia-smi -L GPU 0: NVIDIA Thor (UUID: GPU-a7c66ad2-6dbb-0ab8-c1a2-37ba6dba3600) nvidia@localhost:~$ sudo nvidia-smi -L GPU 0: NVIDIA Thor (UUID: GPU-a7c66ad2-6dbb-0ab8-c1a2-37ba6dba3600) nvidia@localhost:~$ nvidia-smi Fri Jul 24 12:00:54 2026 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 580.00 Driver Version: 580.00 CUDA Version: 13.0 | +-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA Thor Off | 00000000:01:00.0 Off | N/A | | N/A 40C N/A 3W / N/A | Not Supported | N/A Default | | | | Enabled | +-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+ | MIG devices: | +------------------+----------------------------------+-----------+-----------------------+ | GPU GI CI MIG | Shared Memory-Usage | Vol| Shared | | ID ID Dev | Shared BAR1-Usage | SM Unc| CE ENC DEC OFA JPG | | | | ECC| | |==================+==================================+===========+=======================| | No MIG devices found | +-----------------------------------------------------------------------------------------+
+-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | No running processes found | +-----------------------------------------------------------------------------------------+ nvidia@localhost:~$ nvidia-smi mig -lgip +-------------------------------------------------------------------------------+ | GPU instance profiles: | | GPU Name ID Instances Memory P2P SM DEC ENC | | Free/Total GiB CE JPEG OFA | |===============================================================================| Failed to display GPU instance profiles: Unknown Error nvidia@localhost:~$ sudo nvidia-smi mig -lgip +-------------------------------------------------------------------------------+ | GPU instance profiles: | | GPU Name ID Instances Memory P2P SM DEC ENC | | Free/Total GiB CE JPEG OFA | |===============================================================================| Failed to display GPU instance profiles: Unknown Error
nvidia@localhost:~$ sudo nvidia-smi -pm 1 Enabled Legacy persistence mode for GPU 00000000:01:00.0. All done. nvidia@localhost:~$ sudo nvidia-smi -i 0 -mig 1 Enabled MIG Mode for GPU 00000000:01:00.0 All done. nvidia@localhost:~$ sudo nvidia-smi mig -lgip +-------------------------------------------------------------------------------+ | GPU instance profiles: | | GPU Name ID Instances Memory P2P SM DEC ENC | | Free/Total GiB CE JPEG OFA | |===============================================================================| Failed to display GPU instance profiles: Unknown Error
driver 버전은 이런데..
NVIDIA-SMI 580.00 Driver Version: 580.00 CUDA Version: 13.0
nvidia@nvidia:~$ nvidia-smi -i 0 -mig 1 Unable to enable MIG Mode for GPU 00000000:01:00.0: Insufficient Permissions Terminating early due to previous errors. nvidia@nvidia:~$ nvidia-smi -L GPU 0: NVIDIA Thor (UUID: GPU-a7c66ad2-6dbb-0ab8-c1a2-37ba6dba3600) nvidia@nvidia:~$ nvidia-smi mig -lgip +-------------------------------------------------------------------------------+ | GPU instance profiles: | | GPU Name ID Instances Memory P2P SM DEC ENC | | Free/Total GiB CE JPEG OFA | |===============================================================================| nvidia@nvidia:~$ sudo nvidia-smi mig -lgip +-------------------------------------------------------------------------------+ | GPU instance profiles: | | GPU Name ID Instances Memory P2P SM DEC ENC | | Free/Total GiB CE JPEG OFA | |===============================================================================| nvidia@nvidia:~$ nvidia-smi mig
mig -- Multi Instance GPU management.
Usage: nvidia-smi mig [options]
Options include: [-h | --help]: Display help information. [-i | --id]: Enumeration index, PCI bus ID or UUID. Provide comma separated values for more than one device. [-gi | --gpu-instance-id]: GPU instance ID. Provide comma separated values for more than one GPU instance. [-ci | --compute-instance-id]: Compute instance ID. Provide comma separated values for more than one compute instance. [-lgip | --list-gpu-instance-profiles]: List supported GPU instance profiles. Option -i can be used to restrict the command to run on a specific GPU. [-lgipp | --list-gpu-instance-possible-placements]: List possible GPU instance placements in the following format, {Start}:Size. Option -i can be used to restrict the command to run on a specific GPU. [-C | --default-compute-instance]: Create compute instance with the default profile when used with the option to create a GPU instance (-cgi). [-cgi | --create-gpu-instance]: Create GPU instances for the given profile tuples. A profile tuple consists of a profile name or ID and an optional placement specifier, which consists of a colon and a placement start index. Provide comma separated values for more than one profile tuple. Option -i can be used to restrict the command to run on a specific GPU. [-dgi | --destroy-gpu-instance]: Destroy GPU instances. Options -i and -gi can be used individually or combined to restrict the command to run on a specific GPU or GPU instance. [-lgi | --list-gpu-instances]: List GPU instances. Option -i can be used to restrict the command to run on a specific GPU. [-lcip | --list-compute-instance-profiles]: List supported compute instance profiles. Options -i and -gi can be used individually or combined to restrict the command to run on a specific GPU or GPU instance. [-lcipp | --list-compute-instance-possible-placements]: List possible compute instance placements in the following format, {Start}:Size. Options -i and -gi can be used individually or combined to restrict the command to run on a specific GPU or GPU instance. [-cci | --create-compute-instance]: Create compute instance for the given profile name or IDs. Provide comma separated values for more than one profile. If no profile name or ID is given, then the default* compute instance profile ID will be used. Options -i and -gi can be used individually or combined to restrict the command to run on a specific GPU or GPU instance. [-dci | --destroy-compute-instance]: Destroy compute instances. Options -i, -gi and -ci can be used individually or combined to restrict the command to run on a specific GPU or GPU instance or compute instance. [-lci | --list-compute-instances]: List compute instances. Options -i and -gi can be used individually or combined to restrict the command to run on a specific GPU or GPU instance.
persistent mode를 활성화 해주어야 한다. 물론 persistent mode 한다고 해서
전원 off 하고 다시 켠다고 또 되는건 아닌듯. 그럼 왜 persistent mode라고 하는겨?
$ sudo nvidia-smi mig -cgi 80,83 Successfully created GPU instance ID 2 on GPU 0 using profile MIG 1g.0gb (ID 80) Successfully created GPU instance ID 1 on GPU 0 using profile MIG 2g.0gb+gfx (ID 83) nvidia@nvidia:~$ nvidia-smi Fri Jul 24 17:50:43 2026 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 595.78 Driver Version: 595.78 CUDA Version: 13.2 | +-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA Thor On | 00000000:01:00.0 Off | N/A | | N/A 42C N/A 4W / N/A | Not Supported | N/A Default | | | | Enabled | +-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+ | MIG devices: | +------------------+----------------------------------+-----------+-----------------------+ | GPU GI CI MIG | Shared Memory-Usage | Vol| Shared | | ID ID Dev | Shared BAR1-Usage | SM Unc| CE ENC DEC OFA JPG | | | | ECC| | |==================+==================================+===========+=======================| | No MIG devices found | +-----------------------------------------------------------------------------------------+
+-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | No running processes found | +-----------------------------------------------------------------------------------------+
nvidia@nvidia:~$ sudo nvidia-smi mig -cgi 80,83 -C Successfully created GPU instance ID 2 on GPU 0 using profile MIG 1g.0gb (ID 80) Successfully created compute instance ID 0 on GPU 0 GPU instance ID 2 using profile MIG 1g.0gb (ID 0) Successfully created GPU instance ID 1 on GPU 0 using profile MIG 2g.0gb+gfx (ID 83) Successfully created compute instance ID 0 on GPU 0 GPU instance ID 1 using profile MIG 2g.0gb (ID 1) nvidia@nvidia:~$ nvidia-smi Fri Jul 24 17:53:35 2026 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 595.78 Driver Version: 595.78 CUDA Version: 13.2 | +-----------------------------------------+------------------------+----------------------+ | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA Thor On | 00000000:01:00.0 Off | N/A | | N/A 41C N/A 4W / N/A | Not Supported | N/A Default | | | | Enabled | +-----------------------------------------+------------------------+----------------------+
nvidia@localhost:~$ cat /proc/cpuinfo processor : 0 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 1 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 2 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 3 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 4 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 5 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 6 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 7 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 8 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 9 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 10 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 11 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 12 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
processor : 13 BogoMIPS : 2000.00 Features : fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma lrcpc dcpop sha3 sm3 sm4 asimddp sha512 sve asimdfhm dit uscat ilrcpc flagm ssbs sb paca pacg dcpodp sve2 sveaes svepmull svebitperm svesha3 svesm4 flagm2 frint svei8mm svebf16 i8mm bf16 dgh bti ecv afp wfxt CPU implementer : 0x41 CPU architecture: 8 CPU variant : 0x0 CPU part : 0xd83 CPU revision : 0
$ sudo dmidecode # dmidecode 3.5 Getting SMBIOS data from sysfs. SMBIOS 3.6.0 present. # SMBIOS implementations newer than version 3.5.0 are not # fully supported by this version of dmidecode. Table at 0x1FBB130000.
Handle 0x0000, DMI type 0, 26 bytes BIOS Information Vendor: EDK II Version: 38.4.0-gcid-43443517 Release Date: 12/30/2025 ROM Size: 0 MB Characteristics: PCI is supported PNP is supported BIOS is upgradeable BIOS shadowing is allowed Boot from CD is supported Selectable boot is supported ACPI is supported Targeted content distribution is supported UEFI is supported BIOS Revision: 0.0 Firmware Revision: 0.0
Handle 0x0001, DMI type 1, 27 bytes System Information Manufacturer: NVIDIA Product Name: NVIDIA Jetson AGX Thor Developer Kit Version: Not Specified Serial Number: 1423525040774 UUID: 5ecc6819-51f8-517e-b26f-0f0163b2c9ab Wake-up Type: Power Switch SKU Number: Unknown Family: Unknown
Handle 0x0002, DMI type 3, 25 bytes Chassis Information Manufacturer: NVIDIA Type: Other Lock: Not Present Version: Unknown Serial Number: Unknown Asset Tag: 699-13834-0008-400 H.1 Boot-up State: Unknown Power Supply State: Unknown Thermal State: Unknown Security Status: Unknown OEM Information: 0x00000000 Height: 1 U Number Of Power Cords: 1 Contained Elements: 0 SKU Number: Unknown
Handle 0x0003, DMI type 2, 17 bytes Base Board Information Manufacturer: NVIDIA Product Name: Jetson Version: Not Specified Serial Number: 1423525040774 Asset Tag: 699-13834-0008-400 H.1 Features: Board is a hosting board Board is replaceable Location In Chassis: Unknown Chassis Handle: 0x0002 Type: Motherboard Contained Object Handles: 0
Handle 0x0004, DMI type 13, 22 bytes BIOS Language Information Language Description Format: Long Installable Languages: 1 en|US|iso8859-1 Currently Installed Language: en|US|iso8859-1
Handle 0x0005, DMI type 32, 11 bytes System Boot Information Status: No errors detected
Handle 0x0009, DMI type 4, 50 bytes Processor Information Socket Designation: Not Specified Type: Central Processor Family: ARMv8 Manufacturer: NVIDIA ID: 64 02 6B 03 01 04 00 00 Signature: JEP-106 Bank 0x03 Manufacturer 0x6b, SoC ID 0x0264, SoC Revision 0x00000401 Version: Thor Voltage: Unknown External Clock: 1000 MHz Max Speed: 2601 MHz Current Speed: 2601 MHz Status: Populated, Enabled Upgrade: Unknown L1 Cache Handle: 0x0007 L2 Cache Handle: 0x0008 L3 Cache Handle: Not Provided Serial Number: Not Specified Asset Tag: Not Specified Part Number: Not Specified Core Count: 14 Core Enabled: 14 Thread Count: 14 Characteristics: 64-bit capable Multi-Core Execute Protection Enhanced Virtualization Arm64 SoC ID
Handle 0x000A, DMI type 16, 23 bytes Physical Memory Array Location: System Board Or Motherboard Use: System Memory Error Correction Type: Single-bit ECC Maximum Capacity: 128 GB Error Information Handle: Not Provided Number Of Devices: 1
cd ~ git clone https://github.com/KhronosGroup/glslang.git cd glslang python3 update_glslang_sources.py mkdir build && cd build export LDFLAGS="-lstdc++fs" /opt/cmake/bin/cmake .. -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=/usr/local \ -DCMAKE_C_COMPILER=gcc-9 -DCMAKE_CXX_COMPILER=g++-9 make -j$(nproc) sudo make install which glslangValidator
shaderc 설치
cd ~ git clone https://github.com/google/shaderc.git cd shaderc python3 utils/git-sync-deps mkdir build && cd build export LDFLAGS="-lstdc++fs" /opt/cmake/bin/cmake .. -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=/usr/local \ -DCMAKE_C_COMPILER=gcc-9 -DCMAKE_CXX_COMPILER=g++-9 \ -DSHADERC_SKIP_TESTS=ON -DSHADERC_SKIP_EXAMPLES=ON \ -DSPIRV_SKIP_EXECUTABLES=ON make glslc_exe -j$(nproc) sudo cp glslc/glslc /usr/local/bin/ which glslc glslc --version
$ git status On branch master Your branch is up to date with 'origin/master'.
Changes not staged for commit: (use "git add <file>..." to update what will be committed) (use "git checkout -- <file>..." to discard changes in working directory)
build : b10068-571d0d540 model : /home/jetson/llm/Qwen3.5-0.8B-Q4_0.gguf ftype : Q4_0 modalities : text
available commands: /exit or Ctrl+C stop or exit /regen regenerate the last response /clear clear the chat history /read <file> add a text file /glob <pattern> add text files using globbing pattern
> 안녕? 안녕하세요! 어시, 어떻게 도와드릴 수 있을까요?
[ Prompt: 21.4 t/s | Generation: 9.1 t/s ]
> 안녕? 안녕하세요! 어시, 어떻게 도와드릴 수 있을까요?
[ Prompt: 23.0 t/s | Generation: 9.1 t/s ]
> 너에 대해 소개 안녕하세요! 저는 인공지능(AI) 기술의 능력을 활용하여 정보를 제공하거나 논리적 사고를 도와줄 수 있는 **공급 서비스 봇 (Assistant)**입니다.
나는 다음과 같은 역할을 수행할 수 있습니다: * **정보 제공**: 지식 기반의 정보를 검색하고 요약 또는 정리해 줄 수 있습니다. * **논리적 분석**: 문장 구조나 논리 논리를 분석하여 설명을 돕습니다. * **문제 해결**: 질문에 답하거나 상황을 분석할 수 있습니다. * **대화 및 학습**: 대화와 학습을 통해 사용자 경험을 개선해 줍니다.
이러한 기능을 통해 **AI**를 대신할 수 있는 인간과 유사한 능력으로 **사용자**에게 도움을 줄 수 있습니다.
어떤 내용을 원하시는가요? (예: 답변, 설명, 대화, 학습 자료 등)
[ Prompt: 21.8 t/s | Generation: 8.5 t/s ]
> 코드 작성 python hello world 출력 네, 안녕하세요! 저는 인공지능(AI) 기술의 능력을 활용하여 정보를 제공하거나 논리적 사고를 도와드릴 수 있는 서비스 봇입니다.
제대안은 **Python**을 사용하여 `print` 함수로 `hello world`를 출력하는 코드를 작성해 드립니다.
```python print("hello world") ```
이 코드를 실행하면 다음 문장이 출력됩니다: `hello world`
혹시 다른 언어 (예: JavaScript, Java 등) 의 `hello world` 예제를 작성하고 싶으시다면 말씀해 주세요!
build : b10068-571d0d540 model : /home/jetson/llm/Qwen3.5-0.8B-Q4_0.gguf ftype : Q4_0 modalities : text
available commands: /exit or Ctrl+C stop or exit /regen regenerate the last response /clear clear the chat history /read <file> add a text file /glob <pattern> add text files using globbing pattern
> 안녕? 안녕하세요! 네, 알겠습니다. 저는 인공지능으로 대화하고 정보를 제공해 드릴 수 있는 도구입니다. 무엇을 도와드릴까요? 😊
[ Prompt: 5.9 t/s | Generation: 3.3 t/s ]
> 너에 대해 소개해줘 안녕하세요! 네, 알겠습니다. 저는 인공지능으로 대화하고 정보를 제공해 드릴 수 있는 도구입니다. 무엇을 도와드릴까요? 😊
[ Prompt: 9.2 t/s | Generation: 3.3 t/s ]
> 파이썬으로 현재 디렉토리 목록 보는 프로그램 작서앻줘ㅏ 프라이썬으로 현재 디렉토리 목록을 보고 싶으신가요? 😊
이제 바로 `dir` 명령어에 대한 설명부터 실행 방법까지 알려드릴게요.
### 📂 디렉토리 목록을 표시하는 명령어
프라이썬에서 파일이나 디렉토리를 표시하려면 먼저 `dir` 명령어를 사용합니다.
```bash cd <디렉토리명> ```
예를 들어, `C:\Users\박\Documents`를 표시하려면: ```bash cd C:\Users\박\Documents ``` **단순히 `dir`을 입력하면 현재 디렉토리를 표시할 수 있습니다.**
---
### 🛠️ 실행 방법
#### 1. **프라이썬을 실행하기** 프라이썬은 웹 브라우저로 작동하는 프로그램으로, 브라우저에서 직접 실행해 볼 수 있습니다.
**단순 브라우저에서 실행하기:** * **Chrome/Edge/ChromeOS:** `https://www.python.org/` 에서 `dir` 명령어 추가하기 (F12 또는 `F11`를 누ار) * **Mac OS:** `Finder` → `Extensions` → `File Explorer` → `Python` → `dir`
**프라이썬을 설치하기:** 1. `https://www.python.org/` 에서 `Install Python` 클릭 2. 설치 후 `~` 경로에 추가되면, 브라우저에서 `file://` 주소창을 입력하고 입력한 URL 을 보시면 됩니다.
---
### 💻 기본 실행 예시
```python # 위 설명에서 예시처럼, 현재 디렉토리를 확인 dir ```
혹시 특정 파일이나 디렉토리를 찾으셨다면 `dir` 대신 `find` 명령어도 사용할 수 있습니다. ```bash find <디렉토리명> -name "파일명" ```
$ sudo nvpmodel -q NVPM WARN: fan mode is not set! NV Power Mode: MAXN 0
docker 로 서비스 실행
$ sudo docker run -p 8080:8080 -v /home/jetson/llm:/models ghcr.io/ggml-org/llama.cpp:server-vulkan --chat-template-kwargs "{\"enable_thinking\": false}" -m /models/Qwen3.5-0.8B-Q4_0.gguf -c 4096 --port 8080 --host 0.0.0.0 warn: LLAMA_ARG_HOST environment variable is set, but will be overwritten by command line argument --host 0.00.136.037 W Setting 'enable_thinking' via --chat-template-kwargs is deprecated. Use --reasoning on / --reasoning off instead. 0.00.136.924 I cmn common_param: common_params_print_info: verbosity = 3 (adjust with the `-lv N` CLI arg) 0.00.138.536 W srv llama_server: ----------------- 0.00.138.551 W srv llama_server: CORS is set to allow all origins ('*') and no API key is set 0.00.138.552 W srv llama_server: this can be a security risk (cross-origin attacks) 0.00.138.553 W srv llama_server: more info: https://github.com/ggml-org/llama.cpp/pull/25655 0.00.138.554 W srv llama_server: ----------------- 0.00.139.997 I srv load_model: loading model '/models/Qwen3.5-0.8B-Q4_0.gguf' 0.04.582.967 I srv load_model: initializing, n_slots = 4, n_ctx_slot = 4096, kv_unified = 'true' 0.04.681.224 I srv llama_server: model loaded 0.04.681.254 I srv llama_server: listening on http://0.0.0.0:8080 0.19.911.095 I slot get_availabl: id 3 | task -1 | selected slot by LRU, t_last = -1 0.19.911.286 I slot launch_slot_: id 3 | task 0 | processing task, is_child = 0 0.22.612.244 I slot print_timing: id 3 | task 0 | prompt eval time = 1093.85 ms / 13 tokens ( 84.14 ms per token, 11.88 tokens per second) 0.22.612.263 I slot print_timing: id 3 | task 0 | eval time = 1606.96 ms / 12 tokens ( 133.91 ms per token, 7.47 tokens per second) 0.22.612.266 I slot print_timing: id 3 | task 0 | total time = 2700.81 ms / 25 tokens 0.22.612.276 I slot print_timing: id 3 | task 0 | graphs reused = 11 0.22.612.345 I slot release: id 3 | task 0 | stop processing: n_tokens = 24, truncated = 0 0.32.329.433 I slot get_availabl: id 3 | task -1 | selected slot by LCP similarity, sim_best = 0.243 (> 0.100 thold), f_keep = 0.375 0.32.406.612 I slot launch_slot_: id 3 | task 14 | processing task, is_child = 0 0.37.382.135 I slot print_timing: id 3 | task 14 | prompt eval time = 2254.95 ms / 28 tokens ( 80.53 ms per token, 12.42 tokens per second) 0.37.382.154 I slot print_timing: id 3 | task 14 | eval time = 2720.41 ms / 18 tokens ( 151.13 ms per token, 6.62 tokens per second) 0.37.382.157 I slot print_timing: id 3 | task 14 | total time = 4975.37 ms / 46 tokens 0.37.382.160 I slot print_timing: id 3 | task 14 | graphs reused = 27 0.37.382.205 I slot release: id 3 | task 14 | stop processing: n_tokens = 54, truncated = 0 0.52.606.713 I slot get_availabl: id 3 | task -1 | selected slot by LCP similarity, sim_best = 0.471 (> 0.100 thold), f_keep = 0.611 0.52.606.847 I slot launch_slot_: id 3 | task 35 | processing task, is_child = 0 1.10.385.311 I slot print_timing: id 3 | task 35 | n_decoded = 100, tg = 6.70 t/s, tg_3s = 6.70 t/s 1.11.031.932 I slot print_timing: id 3 | task 35 | prompt eval time = 2847.89 ms / 37 tokens ( 76.97 ms per token, 12.99 tokens per second) 1.11.031.951 I slot print_timing: id 3 | task 35 | eval time = 15577.07 ms / 104 tokens ( 149.78 ms per token, 6.68 tokens per second) 1.11.031.954 I slot print_timing: id 3 | task 35 | total time = 18424.96 ms / 141 tokens 1.11.031.960 I slot print_timing: id 3 | task 35 | graphs reused = 129 1.11.032.011 I slot release: id 3 | task 35 | stop processing: n_tokens = 173, truncated = 0 3.50.029.790 I slot get_availabl: id 3 | task -1 | selected slot by LCP similarity, sim_best = 0.333 (> 0.100 thold), f_keep = 0.382 3.50.175.603 I slot launch_slot_: id 3 | task 142 | processing task, is_child = 0 3.57.905.059 I slot print_timing: id 3 | task 142 | prompt processing, n_tokens = 105, progress = 0.86, t = 7.73 s / 13.58 tokens per second 3.59.618.519 I slot print_timing: id 3 | task 142 | prompt processing, n_tokens = 128, progress = 0.98, t = 9.44 s / 13.56 tokens per second 4.10.877.834 I slot print_timing: id 3 | task 142 | prompt eval time = 9819.15 ms / 132 tokens ( 74.39 ms per token, 13.44 tokens per second) 4.10.877.855 I slot print_timing: id 3 | task 142 | eval time = 10882.92 ms / 72 tokens ( 151.15 ms per token, 6.62 tokens per second) 4.10.877.858 I slot print_timing: id 3 | task 142 | total time = 20702.07 ms / 204 tokens 4.10.877.862 I slot print_timing: id 3 | task 142 | graphs reused = 198 4.10.877.944 I slot release: id 3 | task 142 | stop processing: n_tokens = 269, truncated = 0
Jetson Nano는 Maxwell 아키텍처 기반 GPU(128 CUDA 코어)를 사용하며, compute capability는 5.3입니다.
CUDA 버전
Jetson Nano는 JetPack 버전에 따라 CUDA 버전이 결정됩니다. Nano에서 지원되는 마지막(최신) JetPack은 JetPack 4.6.x 계열이며, 이때 CUDA 10.2가 탑재됩니다. 참고로 Jetson Nano는 32비트 시절부터 나온 구형 라인업(2019년 출시)이라 JetPack 5.x(CUDA 11.x 이상)는 지원하지 않습니다. JetPack 5 이상은 Xavier, Orin 계열부터 지원됩니다
netson nano / maxwell 기반 128 cuda core
GPU NVIDIA Maxwell architecture with 128 NVIDIA CUDA® cores CPU Quad-core ARM Cortex-A57 MPCore processor Memory 4 GB 64-bit LPDDR4, 1600MHz 25.6 GB/s
$ cat /etc/nv_tegra_release # R32 (release), REVISION: 7.1, GCID: 29818004, BOARD: t210ref, EABI: aarch64, DATE: Sat Feb 19 17:05:08 UTC 2022
$ nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2021 NVIDIA Corporation Built on Sun_Feb_28_22:34:44_PST_2021 Cuda compilation tools, release 10.2, V10.2.300 Build cuda_10.2_r440.TC440_70.29663091_0
b10068 인데 cuda 12 와 cuda 13에 대해서 지원한다.
소스에서 빌드한다고 해서 될 게 아닌듯..
Windows:
Windows x64 (CPU) Windows arm64 (CPU) Windows arm64 (OpenCL Adreno) Windows x64 (CUDA 12) - CUDA 12.4 DLLs Windows x64 (CUDA 13) - CUDA 13.3 DLLs Windows x64 (Vulkan) Windows x64 (OpenVINO) Windows x64 (SYCL) Windows x64 (HIP)
[ 5%] Building CXX object tools/ui/CMakeFiles/llama-ui-embed.dir/embed.cpp.o /home/jetson/src/llama.cpp/tools/ui/embed.cpp:17:10: fatal error: filesystem: No such file or directory #include <filesystem> ^~~~~~~~~~~~ compilation terminated.
$ g++ --version g++ (Ubuntu/Linaro 7.5.0-3ubuntu1~18.04) 7.5.0 Copyright (C) 2017 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
$ sudo apt install gcc-8 g++-8
$ sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-8 800 --slave /usr/bin/g++ g++ /usr/bin/g++-8 update-alternatives: using /usr/bin/gcc-8 to provide /usr/bin/gcc (gcc) in auto mode
$ g++ --version g++ (Ubuntu/Linaro 8.4.0-1ubuntu1~18.04) 8.4.0 Copyright (C) 2018 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
