อุปกรณ์ฮาร์ดแวร์ 10 อย่าง

อุปกรณ์ฮาร์ดแวร์ 10 อย่าง

อุปกรณ์ฮาร์ดแวร์คอมพิวเตอร์ CPU RAM Motherboard Storage SSD HDD GPU Power Supply Case Cooling Monitor Peripheral

CPU และ GPU

# hardware_info.py — Hardware Information
from dataclasses import dataclass
from typing import List

@dataclass
class CPU:
    name: str
    cores: int
    threads: int
    base_clock_ghz: float
    boost_clock_ghz: float
    cache_mb: int
    tdp_w: int
    price_thb: int
    use_case: str

cpus = [
    CPU("Intel Core i5-14400F", 10, 16, 2.5, 4.7, 20, 65, 6500, "เล่นเกม ทั่วไป"),
    CPU("AMD Ryzen 5 7600", 6, 12, 3.8, 5.1, 32, 65, 7500, "เล่นเกม ทั่วไป"),
    CPU("Intel Core i7-14700K", 20, 28, 3.4, 5.6, 33, 125, 13000, "เล่นเกม Streaming"),
    CPU("AMD Ryzen 7 7800X3D", 8, 16, 4.2, 5.0, 96, 120, 13500, "เล่นเกม 3D Cache"),
    CPU("Intel Core i9-14900K", 24, 32, 3.2, 6.0, 36, 125, 19000, "Workstation Rendering"),
    CPU("AMD Ryzen 9 7950X", 16, 32, 4.5, 5.7, 64, 170, 18000, "Workstation Multi-thread"),
]

print("=== CPU Comparison ===")
print(f"{'Name':<26} {'C/T':>5} {'Boost':>5} {'TDP':>4} {'Price':>7} Use")
for cpu in cpus:
    print(f"  {cpu.name:<26} {cpu.cores}/{cpu.threads:>2} {cpu.boost_clock_ghz:>5.1f} "
          f"{cpu.tdp_w:>4}W {cpu.price_thb:>6,} {cpu.use_case}")

@dataclass
class GPU:
    name: str
    vram_gb: int
    cuda_cores: int
    clock_mhz: int
    tdp_w: int
    price_thb: int
    use_case: str

gpus = [
    GPU("RTX 4060", 8, 3072, 2460, 115, 11000, "1080p Gaming"),
    GPU("RTX 4070", 12, 5888, 2475, 200, 19000, "1440p Gaming"),
    GPU("RTX 4070 Ti Super", 16, 8448, 2610, 285, 27000, "1440p/4K Gaming"),
    GPU("RTX 4080 Super", 16, 10240, 2550, 320, 35000, "4K Gaming"),
    GPU("RTX 4090", 24, 16384, 2520, 450, 60000, "4K Gaming AI"),
    GPU("RX 7800 XT", 16, 3840, 2430, 263, 17000, "1440p Gaming คุ้มค่า"),
]

print(f"\n=== GPU Comparison ===")
print(f"{'Name':<22} {'VRAM':>5} {'TDP':>4} {'Price':>7} Use")
for gpu in gpus:
    print(f"  {gpu.name:<22} {gpu.vram_gb:>3}GB {gpu.tdp_w:>4}W {gpu.price_thb:>6,} {gpu.use_case}")

RAM และ Storage

# storage.py — RAM & Storage Comparison
@dataclass
class RAMConfig:
    name: str
    capacity_gb: int
    speed_mhz: int
    type: str
    channels: int
    price_thb: int

rams = [
    RAMConfig("DDR4 16GB Kit", 16, 3200, "DDR4", 2, 1500),
    RAMConfig("DDR4 32GB Kit", 32, 3600, "DDR4", 2, 3000),
    RAMConfig("DDR5 16GB Kit", 16, 5600, "DDR5", 2, 2200),
    RAMConfig("DDR5 32GB Kit", 32, 6000, "DDR5", 2, 4000),
    RAMConfig("DDR5 64GB Kit", 64, 5600, "DDR5", 2, 7500),
]

print("=== RAM Options ===")
for ram in rams:
    print(f"  {ram.name} | {ram.speed_mhz}MHz | {ram.channels}ch | {ram.price_thb:,} THB")

@dataclass
class StorageDevice:
    name: str
    type: str
    capacity_gb: int
    read_speed_mbs: int
    write_speed_mbs: int
    price_thb: int
    interface: str

storages = [
    StorageDevice("Samsung 990 Pro 1TB", "NVMe SSD", 1000, 7450, 6900, 4500, "PCIe 4.0"),
    StorageDevice("WD Black SN850X 2TB", "NVMe SSD", 2000, 7300, 6600, 7000, "PCIe 4.0"),
    StorageDevice("Samsung 870 EVO 1TB", "SATA SSD", 1000, 560, 530, 2800, "SATA III"),
    StorageDevice("Seagate Barracuda 4TB", "HDD", 4000, 190, 190, 3200, "SATA III"),
    StorageDevice("WD Red Plus 8TB", "HDD", 8000, 215, 215, 7500, "SATA III (NAS)"),
]

print(f"\n=== Storage Options ===")
print(f"{'Name':<28} {'Type':<10} {'Read':>5} {'Write':>5} {'Price':>6}")
for s in storages:
    print(f"  {s.name:<28} {s.type:<10} {s.read_speed_mbs:>5} {s.write_speed_mbs:>5} {s.price_thb:>5,}")

# Build Recommendations
builds = {
    "Budget (15K)": {
        "CPU": "i5-14400F / Ryzen 5 7600",
        "RAM": "DDR4/5 16GB",
        "GPU": "RTX 4060 / RX 7600",
        "Storage": "NVMe 500GB + HDD 1TB",
        "PSU": "550W 80+ Bronze",
    },
    "Mid-range (30K)": {
        "CPU": "i7-14700F / Ryzen 7 7800X3D",
        "RAM": "DDR5 32GB",
        "GPU": "RTX 4070 / RX 7800 XT",
        "Storage": "NVMe 1TB",
        "PSU": "750W 80+ Gold",
    },
    "High-end (60K+)": {
        "CPU": "i9-14900K / Ryzen 9 7950X",
        "RAM": "DDR5 64GB",
        "GPU": "RTX 4080 Super / RTX 4090",
        "Storage": "NVMe 2TB",
        "PSU": "1000W 80+ Gold",
    },
}

print(f"\n\n=== Build Recommendations ===")
for tier, specs in builds.items():
    print(f"\n  [{tier}]")
    for part, value in specs.items():
        print(f"    {part}: {value}")

Python Hardware Monitor

# monitor.py — Hardware Monitoring
# pip install psutil GPUtil

# import psutil
# import GPUtil
#
# # CPU Info
# print(f"CPU: {psutil.cpu_count()} cores")
# print(f"CPU Usage: {psutil.cpu_percent(interval=1)}%")
# print(f"CPU Freq: {psutil.cpu_freq().current:.0f} MHz")
#
# # RAM Info
# ram = psutil.virtual_memory()
# print(f"RAM Total: {ram.total / (1024**3):.1f} GB")
# print(f"RAM Used: {ram.used / (1024**3):.1f} GB ({ram.percent}%)")
# print(f"RAM Available: {ram.available / (1024**3):.1f} GB")
#
# # Disk Info
# for partition in psutil.disk_partitions():
#     usage = psutil.disk_usage(partition.mountpoint)
#     print(f"Disk {partition.mountpoint}: "
#           f"{usage.used / (1024**3):.1f}/{usage.total / (1024**3):.1f} GB "
#           f"({usage.percent}%)")
#
# # GPU Info
# gpus = GPUtil.getGPUs()
# for gpu in gpus:
#     print(f"GPU: {gpu.name}")
#     print(f"  VRAM: {gpu.memoryUsed:.0f}/{gpu.memoryTotal:.0f} MB")
#     print(f"  Load: {gpu.load*100:.0f}%")
#     print(f"  Temp: {gpu.temperature}°C")
#
# # Temperature
# temps = psutil.sensors_temperatures()
# for name, entries in temps.items():
#     for entry in entries:
#         print(f"  {name}: {entry.current}°C")

hardware_status = {
    "CPU": {"usage": 35, "temp": 62, "clock": 4500},
    "RAM": {"used_gb": 12.5, "total_gb": 32, "percent": 39},
    "GPU": {"usage": 45, "temp": 68, "vram_used": 4.2, "vram_total": 12},
    "SSD": {"used_gb": 450, "total_gb": 1000, "temp": 42},
}

print("=== Hardware Status ===")
for component, stats in hardware_status.items():
    print(f"\n  [{component}]")
    for stat, value in stats.items():
        print(f"    {stat}: {value}")

เคล็ดลับ

• CPU+GPU Balance: ไม่ใส่ GPU แรงกับ CPU อ่อน จะ Bottleneck
• PSU: เลือก PSU คุณภาพ 80+ Gold ขึ้นไป อย่าประหยัดจุดนี้
• SSD: ติดตั้ง OS บน NVMe SSD เร็วขึ้นมหาศาล
• RAM: ใส่ Dual Channel เร็วกว่า Single Channel
• Cooling: CPU 65W+ ควรมี Tower Cooler หรือ AIO

อุปกรณ์ฮาร์ดแวร์คอมพิวเตอร์มีอะไรบ้าง

CPU RAM Motherboard Storage SSD HDD GPU Power Supply Case Cooling Monitor Peripheral 10 อย่างหลัก

สรุป

อุปกรณ์ฮาร์ดแวร์ 10 อย่าง CPU RAM Motherboard SSD HDD GPU PSU Case Cooling Monitor Build Recommendation Budget Mid High-end Hardware Monitoring Python psutil