728x90

출처

리눅스 확인

bluesanta@bluesanta-AI-Series:~/Application/Llama$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description:    Ubuntu 24.04.3 LTS
Release:        24.04
Codename:       noble
bluesanta@bluesanta-AI-Series:~/Application/Llama$ dkms status
amdgpu/6.16.6-2255209.24.04, 6.14.0-37-generic, x86_64: installed
xrt-amdxdna/2.21.0, 6.14.0-37-generic, x86_64: installed

가상환경 생성

bluesanta@bluesanta-AI-Series:~/Application/Llama$ python3 -m venv .venv
bluesanta@bluesanta-AI-Series:~/Application/Llama$ source .venv/bin/activate

PyTorch 설치 (HX 390/gfx1150 아키텍처용)

(.venv) bluesanta@bluesanta-AI-Series:~/Application/Llama$ pip install torch torchvision torchaudio --index-url https://repo.amd.com/rocm/whl/gfx1150/

설치 확인

gpu_check.py

import sys
import torch

# 시스템 및 PyTorch 정보 출력
print(f"Python Version: {sys.version.split()[0]}")
print(f"PyTorch Version: {torch.__version__}")
print(f"GPU 인식 성공: {torch.cuda.is_available()}")

if torch.cuda.is_available():
    print(f"사용 가능 기기: {torch.cuda.get_device_name(0)}")
else:
    print("현재 GPU를 사용할 수 없습니다. 드라이버나 ROCm 설정을 확인하세요.")
 
 
# 실제 텐서 연산 테스트
if torch.cuda.is_available():
    x = torch.randn(1, 3).to("cuda")
    print("GPU 텐서 연산 테스트 완료:", x)

실행

(.venv) bluesanta@bluesanta-AI-Series:~/Application/Llama$ python gpu_check.py
Python Version: 3.12.3
PyTorch Version: 2.9.1+rocm7.10.0
GPU 인식 성공: True
사용 가능 기기: AMD Radeon 890M Graphics
/home/bluesanta/Application/Llama/gpu_check.py:17: UserWarning: expandable_segments not supported on this platform (Triggered internally at /__w/rockrel/rockrel/external-builds/pytorch/pytorch/c10/hip/HIPAllocatorConfig.h:36.)
  x = torch.randn(1, 3).to("cuda")
GPU 텐서 연산 테스트 완료: tensor([[-0.5998, -1.3418, -0.5339]], device='cuda:0')
[W121 10:44:08.608317046 AllocatorConfig.cpp:28] Warning: PYTORCH_CUDA_ALLOC_CONF is deprecated, use PYTORCH_ALLOC_CONF instead (function operator())

PYTORCH_ALLOC_CONF 환경 변수 추가

~/.bashrc 수정

(.venv) bluesanta@bluesanta-AI-Series:~/Application/Llama$ vi ~/.bashrc

내용

export PYTORCH_ALLOC_CONF="expandable_segments:True"

실행

(.venv) bluesanta@bluesanta-AI-Series:~/Application/Llama$ python gpu_check.py 
Python Version: 3.12.3
PyTorch Version: 2.9.1+rocm7.10.0
GPU 인식 성공: True
사용 가능 기기: AMD Radeon 890M Graphics
GPU 텐서 연산 테스트 완료: tensor([[-1.0138, -0.4262,  1.2874]], device='cuda:0')
728x90
728x90

출처

리눅스 확인

radxa@radxa-dragon-q6a:~$ uname -a
Linux radxa-dragon-q6a 6.17.1-2-qcom #2 SMP PREEMPT_DYNAMIC Thu Oct 23 16:49:22 UTC 2025 aarch64 aarch64 aarch64 GNU/Linux
radxa@radxa-dragon-q6a:~$ cat /etc/issue
Ubuntu 24.04.3 LTS \n \l
 
radxa@radxa-dragon-q6a:~$ cat /etc/*release*
DISTRIB_ID=Ubuntu
DISTRIB_RELEASE=24.04
DISTRIB_CODENAME=noble
DISTRIB_DESCRIPTION="Ubuntu 24.04.3 LTS"
PRETTY_NAME="Ubuntu 24.04.3 LTS"
NAME="Ubuntu"
VERSION_ID="24.04"
VERSION="24.04.3 LTS (Noble Numbat)"
VERSION_CODENAME=noble
ID=ubuntu
ID_LIKE=debian
HOME_URL="https://www.ubuntu.com/"
SUPPORT_URL="https://help.ubuntu.com/"
BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
UBUNTU_CODENAME=noble
LOGO=ubuntu-logo

메모리 용량 확인

radxa@radxa-dragon-q6a:~$ free -h
               total        used        free      shared  buff/cache   available
Mem:            11Gi       418Mi        10Gi        17Mi       239Mi        10Gi
Swap:          5.7Gi          0B       5.7Gi

SPI boot firmware 버전 확인

radxa@radxa-dragon-q6a:~$ sudo dmidecode -s bios-version
6.0.251013.BOOT.MXF.1.0.c1-00364-KODIAKLA-1

GPU 정보

radxa@radxa-dragon-q6a:~$ cat /sys/class/drm/card0/device/uevent
DRIVER=msm_dpu
OF_NAME=display-controller
OF_FULLNAME=/soc@0/display-subsystem@ae00000/display-controller@ae01000
OF_COMPATIBLE_0=qcom,sc7280-dpu
OF_COMPATIBLE_N=1
MODALIAS=of:Ndisplay-controllerT(null)Cqcom,sc7280-dpu

 

728x90
728x90

출처

nfs 패키지 설치

bluesanta@bluesanta-A520M-ITX-ac:~$ sudo apt install nfs-common

NFS 를 통해 공유 폴더 마운트

bluesanta@bluesanta-A520M-ITX-ac:~$ sudo mkdir /share_disk
bluesanta@bluesanta-A520M-ITX-ac:~$ sudo mount -t nfs 192.168.0.58:/volumeUSB2/usbshare /share_disk
728x90
728x90

가상환경 만들기

bluesanta@bluesanta-A520M-ITX-ac:~$ mkdir Application
bluesanta@bluesanta-A520M-ITX-ac:~$ cd Application/
bluesanta@bluesanta-A520M-ITX-ac:~/Application$ mkdir stable_diffusion
bluesanta@bluesanta-A520M-ITX-ac:~/Application$ cd stable_diffusion
bluesanta@bluesanta-A520M-ITX-ac:~/Application/stable_diffusion$ sudo apt install python3-venv
bluesanta@bluesanta-A520M-ITX-ac:~/Application/stable_diffusion$ python3 -m venv .venv
bluesanta@bluesanta-A520M-ITX-ac:~/Application/stable_diffusion$ source .venv/bin/activate
(.venv) bluesanta@bluesanta-A520M-ITX-ac:~/Application/stable_diffusion$

PyTorch 설치 (CUDA 12.x 기반 호환)

현재 PyTorch 공식 빌드는 CUDA 12.4~12.6까지 지원

(.venv) bluesanta@bluesanta-A520M-ITX-ac:~/Application/stable_diffusion$ pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124

Transformer 및 최적화 라이브러리 설치

(.venv) bluesanta@bluesanta-A520M-ITX-ac:~/Application/stable_diffusion$ pip install transformers datasets accelerate

8-bit/4-bit 양자화용

(.venv) bluesanta@bluesanta-A520M-ITX-ac:~/Application/stable_diffusion$ pip install bitsandbytes

LoRA 등 효율적 파인튜닝용

(.venv) bluesanta@bluesanta-A520M-ITX-ac:~/Application/stable_diffusion$ pip install peft

ONNX, OpenVINO 등 하드웨어 가속용

(.venv) bluesanta@bluesanta-A520M-ITX-ac:~/Application/stable_diffusion$ pip install optimum

Flash Attention 설치

RTX 4060은 Ada Lovelace 아키텍처를 사용하므로, Transformer 연산 속도를 획기적으로 높여주는 Flash Attention을 설치

(.venv) bluesanta@bluesanta-A520M-ITX-ac:~/Application/stable_diffusion$ pip install flash-attn --no-build-isolation

CUDA 12.4 설치

cuda_version_check.py

import torch
import torch.backends.cudnn as cudnn

print(f"PyTorch version: {torch.__version__}")
print(f"CUDA available: {torch.cuda.is_available()}")
print(f"GPU Name: {torch.cuda.get_device_name(0)}")
print(f"cuDNN version: {torch.backends.cudnn.version()}")

# 현재 연결된 GPU 장치 수
print(f"Device Count: {torch.cuda.device_count()}")

# 간단한 텐서 연산 테스트
x = torch.randn(3, 3).cuda()
print("Tensor operation success!")

if cudnn.is_acceptable(torch.randn(1, device='cuda')):
    print(f"cuDNN version: {cudnn.version()}")
    print("cuDNN is working perfectly!")

실행

(.venv) bluesanta@bluesanta-A520M-ITX-ac:~/Application/stable_diffusion$ python cuda_version_check.py 
PyTorch version: 2.6.0+cu124
CUDA available: True
GPU Name: NVIDIA GeForce RTX 4060
cuDNN version: 90100
Device Count: 1
Tensor operation success!
cuDNN version: 90100
cuDNN is working perfectly!
728x90
728x90

리눅스 버전 확인

bluesanta@bluesanta-A520M-ITX-ac:~$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description:    Ubuntu 24.04.3 LTS
Release:        24.04
Codename:       noble

NVIDIA 드라이버 버전 확인

bluesanta@bluesanta-A520M-ITX-ac:~$ nvidia-smi
Fri Jan  2 21:13:47 2026       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 580.95.05              Driver Version: 580.95.05      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 GeForce RTX 4060        Off |   00000000:01:00.0 Off |                  N/A |
|  0%   41C    P8            N/A  /  115W |     378MiB /   8188MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
 
+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|    0   N/A  N/A            2210      G   /usr/lib/xorg/Xorg                      183MiB |
|    0   N/A  N/A            2428      G   /usr/bin/gnome-shell                    143MiB |
+-----------------------------------------------------------------------------------------+

CUDA 12.4 설치

NVIDIA 저장소 키 및 리스트 등록

bluesanta@bluesanta-A520M-ITX-ac:~$ sudo apt update
bluesanta@bluesanta-A520M-ITX-ac:~$ sudo apt install build-essential dkms wget
bluesanta@bluesanta-A520M-ITX-ac:~$ wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/x86_64/cuda-ubuntu2404.pin
bluesanta@bluesanta-A520M-ITX-ac:~$ sudo mv cuda-ubuntu2404.pin /etc/apt/preferences.d/cuda-repository-pin-600
bluesanta@bluesanta-A520M-ITX-ac:~$ wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/x86_64/cuda-keyring_1.1-1_all.deb
bluesanta@bluesanta-A520M-ITX-ac:~$ sudo dpkg -i cuda-keyring_1.1-1_all.deb
bluesanta@bluesanta-A520M-ITX-ac:~$ sudo apt update

CUDA 12.4 Toolkit 설치

bluesanta@bluesanta-A520M-ITX-ac:~$ sudo apt install cuda-toolkit-12-4

CUDA Toolkit 설치 여부 확인

bluesanta@bluesanta-A520M-ITX-ac:~$ whereis cuda
cuda: /usr/lib/cuda /usr/include/cuda /usr/local/cuda
bluesanta@bluesanta-A520M-ITX-ac:~$ ls -l /usr/local | grep cuda
lrwxrwxrwx  1 root root   22  1월  2 22:32 cuda -> /etc/alternatives/cuda
lrwxrwxrwx  1 root root   25  1월  2 22:32 cuda-12 -> /etc/alternatives/cuda-12
drwxr-xr-x 15 root root 4096  1월  2 22:32 cuda-12.4

환경 변수 등록

설치가 완료되면 /usr/local/cuda-12.4 폴더가 생성됩니다. 이제 시스템이 이 폴더를 인식하도록 설정

bluesanta@bluesanta-A520M-ITX-ac:~$ vi ~/.bashrc

~/.bashrc 내용 추가

# 파일 맨 아래에 다음 세 줄 추가
export PATH=/usr/local/cuda-12.4/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-12.4/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
export CUDA_HOME=/usr/local/cuda-12.4

CUDA Toolkit 설치 (Ubuntu 24.04 기준) - 위에 설치 된것 같지만 다시 확인 필요

bluesanta@bluesanta-A520M-ITX-ac:~$ sudo apt update
bluesanta@bluesanta-A520M-ITX-ac:~$ sudo apt install build-essential dkms
bluesanta@bluesanta-A520M-ITX-ac:~$ sudo apt install nvidia-cuda-toolkit

cuDNN 9 (CUDA 12용) 설치

bluesanta@bluesanta-A520M-ITX-ac:~$ sudo apt install libcudnn9-cuda-12

설치 확인

bluesanta@bluesanta-A520M-ITX-ac:~$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2024 NVIDIA Corporation
Built on Thu_Mar_28_02:18:24_PDT_2024
Cuda compilation tools, release 12.4, V12.4.131
Build cuda_12.4.r12.4/compiler.34097967_0
728x90
728x90

출처

리눅스 버전 확인

bluesanta@bluesanta-AI-Series:~$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description:    Ubuntu 24.04.3 LTS
Release:        24.04
Codename:       noble
bluesanta@bluesanta-AI-Series:~$ lsmod | grep amdgpu
amdgpu              19836928  5
amddrm_ttm_helper      12288  1 amdgpu
amdttm                131072  2 amdgpu,amddrm_ttm_helper
amddrm_buddy           24576  1 amdgpu
amdxcp                 16384  1 amdgpu
amddrm_exec            12288  1 amdgpu
drm_suballoc_helper    20480  1 amdgpu
amd_sched              61440  1 amdgpu
amdkcl                 36864  4 amd_sched,amdttm,amddrm_exec,amdgpu
drm_panel_backlight_quirks    12288  1 amdgpu
drm_display_helper    278528  1 amdgpu
cec                    94208  2 drm_display_helper,amdgpu
i2c_algo_bit           16384  1 amdgpu
drm_ttm_helper         16384  1 amdgpu
video                  77824  1 amdgpu
bluesanta@bluesanta-AI-Series:~$ dkms status
amdgpu/6.16.6-2255209.24.04, 6.14.0-37-generic, x86_64: installed

ComfyUI 설치

가상환경실행

bluesanta@bluesanta-AI-Series:~$ cd Application/stable_diffusion/
bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ source .venv/bin/activate
(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ 

ComfyUI 다운로드

(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ git clone https://github.com/comfyanonymous/ComfyUI.git

ComfyUI 참조 패키지 설치

(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ cd ComfyUI/
(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion/ComfyUI$ pip install -r requirements.txt

ComfyUI 실행

(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion/ComfyUI$ python main.py
Checkpoint files will always be loaded safely.
Total VRAM 14844 MB, total RAM 29688 MB
pytorch version: 2.9.1+rocm7.10.0
Set: torch.backends.cudnn.enabled = False for better AMD performance.
AMD arch: gfx1150
ROCm version: (7, 2)
Set vram state to: NORMAL_VRAM
Device: cuda:0 AMD Radeon 890M Graphics : native
Using async weight offloading with 2 streams
Enabled pinned memory 28203.0
Using sub quadratic optimization for attention, if you have memory or speed issues try using: --use-split-cross-attention
Python version: 3.12.3 (main, Nov  6 2025, 13:44:16) [GCC 13.3.0]
ComfyUI version: 0.7.0
****** User settings have been changed to be stored on the server instead of browser storage. ******
****** For multi-user setups add the --multi-user CLI argument to enable multiple user profiles. ******
ComfyUI frontend version: 1.35.9
[Prompt Server] web root: /home/bluesanta/Application/stable_diffusion/.venv/lib/python3.12/site-packages/comfyui_frontend_package/static
Total VRAM 14844 MB, total RAM 29688 MB
pytorch version: 2.9.1+rocm7.10.0
Set: torch.backends.cudnn.enabled = False for better AMD performance.
AMD arch: gfx1150
ROCm version: (7, 2)
Set vram state to: NORMAL_VRAM
Device: cuda:0 AMD Radeon 890M Graphics : native
Using async weight offloading with 2 streams
Enabled pinned memory 28203.0
 
Import times for custom nodes:
   0.0 seconds: /home/bluesanta/Application/stable_diffusion/ComfyUI/custom_nodes/websocket_image_save.py
 
Context impl SQLiteImpl.
Will assume non-transactional DDL.
No target revision found.
Starting server
 
To see the GUI go to: http://127.0.0.1:8188

ComfyUI Manager 설치

(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion/ComfyUI$ cd custom_nodes/
(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion/ComfyUI/custom_nodes$ git clone https://github.com/Comfy-Org/ComfyUI-Manager.git
(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion/ComfyUI/custom_nodes$ pip install -r ComfyUI-Manager/requirements.txt
728x90
728x90

출처

리눅스 버전 확인

bluesanta@bluesanta-AI-Series:~$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description:    Ubuntu 24.04.3 LTS
Release:        24.04
Codename:       noble

AMD GPU 드라이버 설치

AMD GPU 설치 프로그램 설치

bluesanta@bluesanta-AI-Series:~$ wget https://repo.radeon.com/amdgpu-install/30.20.1/ubuntu/noble/amdgpu-install_7.1.1.70101-1_all.deb
bluesanta@bluesanta-AI-Series:~$ sudo dpkg -i amdgpu-install_7.1.1.70101-1_all.deb 
[sudo] password for bluesanta: 
Selecting previously unselected package amdgpu-install.
(Reading database ... 215673 files and directories currently installed.)
Preparing to unpack amdgpu-install_7.1.1.70101-1_all.deb ...
Unpacking amdgpu-install (30.20.1.0.30200100-2255209.24.04) ...
Setting up amdgpu-install (30.20.1.0.30200100-2255209.24.04) ...

ROCm 패키지 설치

bluesanta@bluesanta-AI-Series:~$ sudo amdgpu-install --usecase=rocm,hiplibsdk --no-dkms

설치 확인

(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ lsmod | grep amdgpu
amdgpu              19836928  6
amddrm_ttm_helper      12288  1 amdgpu
amdttm                131072  2 amdgpu,amddrm_ttm_helper
amddrm_buddy           24576  1 amdgpu
amdxcp                 16384  1 amdgpu
amddrm_exec            12288  1 amdgpu
drm_suballoc_helper    20480  1 amdgpu
amd_sched              61440  1 amdgpu
amdkcl                 36864  4 amd_sched,amdttm,amddrm_exec,amdgpu
drm_panel_backlight_quirks    12288  1 amdgpu
drm_display_helper    278528  1 amdgpu
cec                    94208  2 drm_display_helper,amdgpu
i2c_algo_bit           16384  1 amdgpu
drm_ttm_helper         16384  1 amdgpu
video                  77824  1 amdgpu
(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ dkms status
amdgpu/6.16.6-2255209.24.04, 6.14.0-37-generic, x86_64: installed

아키텍처 강제 인식

HX 370(gfx1150)은 최신 아키텍처이므로, PyTorch가 이를 인식하도록 환경 변수를 선언해야 합니다. 터미널에서 다음을 입력하거나 .bashrc에 추가

bluesanta@bluesanta-AI-Series:~$ vi ~/.bashrc

.bashrc 파일에 HSA_OVERRIDE_GFX_VERSION 값 설정

export HSA_OVERRIDE_GFX_VERSION=11.5.0

PyTorch 설치

가상환경만들기

bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ sudo apt install python3-venv
bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ python3 -m venv .venv
bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ source .venv/bin/activate
(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ 

ROCm 지원 PyTorch 빌드 및 설치

(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ python -m pip install --index-url https://repo.amd.com/rocm/whl/gfx1150/ torch torchvision torchaudio

적용 확인

(.venv) bluesanta@bluesanta-AI-Series:~/Application/stable_diffusion$ python -c "import torch; print(torch.cuda.is_available())"
True
728x90
728x90

출처

Deadsnakes PPA에서 Python 3.11 저장소에 추가

orangepi@orangepi5-plus:~$ sudo apt install -y software-properties-common
orangepi@orangepi5-plus:~$ sudo add-apt-repository ppa:deadsnakes/ppa -y
orangepi@orangepi5-plus:~$ sudo apt update

설치하기 전에 apt가 PPA에서 패키지를 가져오는지 확인

orangepi@orangepi5-plus:~$ sudo apt policy python3.11
python3.11:
  설치: (없음)
  후보: 3.11.14-1+noble1
  버전 테이블:
     3.11.14-1+noble1 500
        500 https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu noble/main arm64 Packages

Python 3.11 설치

orangepi@orangepi5-plus:~$ sudo apt install python3.11 python3.11-venv python3.11-dev
orangepi@orangepi5-plus:~$ sudo apt install python3.11-dbg python3.11-gdbm python3.11-tk

Python 3.11 설치 확인

orangepi@orangepi5-plus:~$ python3.11 --version
Python 3.11.14
orangepi@orangepi5-plus:~$ python3.11 -c "import ssl, sqlite3, bz2; print('Source build is healthy')"
Source build is healthy

Python 3.11 가상 환경

orangepi@orangepi5-plus:~$ mkdir Llama
orangepi@orangepi5-plus:~$ cd Llama
orangepi@orangepi5-plus:~/Llama$ sudo apt install python3.11-venv
orangepi@orangepi5-plus:~/Llama$ python3.11 -m venv .venv
orangepi@orangepi5-plus:~/Llama$ source .venv/bin/activate
(.venv) orangepi@orangepi5-plus:~/Llama$ python -m pip --version
pip 24.0 from /home/orangepi/Llama/.venv/lib/python3.11/site-packages/pip (python 3.11)

Bootstrap Pip with get-pip.py

orangepi@orangepi5-plus:~$ wget https://bootstrap.pypa.io/get-pip.py
orangepi@orangepi5-plus:~$ python3.11 get-pip.py
orangepi@orangepi5-plus:~$ rm get-pip.py
728x90

+ Recent posts