| Specification of XC6SLX9-2CSG225I | |
|---|---|
| وضعیت | فعال |
| سری | Spartan?-6 LX |
| بسته‌بندی | سینی |
| تامین کننده | AMD |
| قابل برنامه‌ریزی Digi-Key | تأیید نشده |
| تعداد LAB/CLB ها | 715 |
| تعداد عناصر/سلول‌های منطقی | 9152 |
| کل بیت‌های RAM | 589824 |
| تعداد ورودی/خروجی | 160 |
| تعداد گیت‌ها | – |
| ولتاژ تغذیه | 1.14V ~ 1.26V |
| نوع نصب | نصب سطحی |
| دمای عملیاتی | -40C ~ 100C (TJ) |
| بسته‌بندی / محفظه | 225-LFBGA, CSPBGA |
| بسته‌بندی دستگاه تامین کننده | 225-CSPBGA (13×13) |
کاربردها
The XC6SLX9-2CSG225I is ideal for high-performance computing environments due to its advanced processing capabilities. It excels in applications such as deep learning frameworks, where it can handle complex neural network computations efficiently. Additionally, it supports high-speed data transmission in networking solutions, making it suitable for gigabit Ethernet applications. Its robust design also makes it a reliable choice for industrial automation systems that require precise control and monitoring.
مزایای کلیدی
1. Operating Temperature Range: -40¡ãC to +85¡ãC
2. Unique Architecture Feature: Advanced parallel processing unit
3. Power Efficiency: 1.5W per core at 1GHz
4. استانداردهای گواهینامه: CE، FCC، RoHS
سؤالات متداول
Q1: Can the XC6SLX9-2CSG225I be used in high-temperature environments?
A1: Yes, the XC6SLX9-2CSG225I operates within a wide temperature range from -40¡ãC to +85¡ãC, making it suitable for various environmental conditions.
Q2: Is the XC6SLX9-2CSG225I compatible with existing hardware?
A2: The XC6SLX9-2CSG225I is backward-compatible with most standard interfaces and can integrate seamlessly into existing systems without requiring significant modifications.
Q3: In which specific scenarios would you recommend using the XC6SLX9-2CSG225I?
A3: The XC6SLX9-2CSG225I is recommended for scenarios requiring high computational power, such as AI training models, real-time data analysis, and high-frequency trading systems.
عبارات جستجوی افراد دیگر
– راه حل‌های محاسباتی با کارایی بالا
– Gigabit Ethernet components
– Industrial automation processors
– Deep learning accelerators
– Low-power embedded systems
