Parameters |
Factory Lead Time |
1 Week |
Surface Mount |
YES |
Published |
2016 |
Number of Terminations |
672 |
HTS Code |
8542.39.00.01 |
Subcategory |
Field Programmable Gate Arrays |
Technology |
CMOS |
Terminal Position |
BOTTOM |
Terminal Form |
BALL |
Peak Reflow Temperature (Cel) |
NOT SPECIFIED |
Supply Voltage |
0.9V |
Terminal Pitch |
1mm |
Time@Peak Reflow Temperature-Max (s) |
NOT SPECIFIED |
JESD-30 Code |
S-PBGA-B672 |
Number of Outputs |
240 |
Qualification Status |
Not Qualified |
Operating Temperature (Max) |
100°C |
Operating Temperature (Min) |
-40°C |
Supply Voltage-Max (Vsup) |
0.93V |
Power Supplies |
0.9V |
Temperature Grade |
INDUSTRIAL |
Supply Voltage-Min (Vsup) |
0.87V |
Number of Inputs |
240 |
Programmable Logic Type |
FIELD PROGRAMMABLE GATE ARRAY |
Number of Logic Cells |
270000 |
Height Seated (Max) |
3.25mm |
Length |
27mm |
Width |
27mm |
RoHS Status |
Non-RoHS Compliant |
This SoC is built on core processor(s).
A 0.9V power supply is recommended.An excessive voltage of 0.93V is considered unsafe for the SoCs wireless, so voltages higher than that are not allowed.At least 0.87V can be supplied as a power source.FIELD PROGRAMMABLE GATE ARRAY can be re-configured to serve different design needs.In total, there are 672 terminations, so system on a chip is really aided by this.Likewise, it has a remarkable system on a chip capability, just like other high-quality Field Programmable Gate Arrays.It is possible to use this SoC chip with 240 outputs.There is 0.9V power supply requirement for this system on chip SoC.There are 240 inputs available on the SoC chip.System on chips of logic are comprised of 270000 logic cells.Temperatures over 100°C may compromise this SoC on chip's performance.The system on a chip SoC is prone to malfunctioning if the temperature decreases below -40°C.
processor.
There are a lot of Altera
10AS027E4F27I3LG System On Chip (SoC) applications.
- Wireless sensor networks
- AC drive control module
- Multiprocessor system-on-chips (MPSoCs)
- Industrial automation devices
- Industrial
- Fitness
- Deep learning hardware
- Efficient hardware for inference of neural networks
- Digital Media
- External USB hard disk/SSD