High Volume Data Processing

High volume data processing starts with the data path

Efficient high volume data processing starts with understanding where data enters the system, how quickly it arrives and which operations need to be performed. 

Processing power alone is not enough. Memory bandwidth, interfaces, buffering and data transport must all keep pace with the incoming data.

Processing data close to the source

Moving every bit of raw data through a system is often inefficient. Processing data close to the source can reduce the amount of information that needs to be transferred, stored or handled elsewhere.

FPGA technology is well suited to parallel operations, while processors can handle more dynamic tasks. Combining both enables TOPIC to process multiple high-bandwidth data streams efficiently.

Large scale data processing without bottlenecks

Large scale data processing depends on balance throughout the complete architecture. PCIe, Ethernet, memory, storage, processors and FPGA logic all need sufficient bandwidth to prevent bottlenecks.

TOPIC designs these elements as one system. By considering the complete data path, processing workloads can be distributed more effectively and unnecessary data movement can be reduced.

Scaling data processing efficiently

As data volumes increase, architectures need to scale without becoming unnecessarily complex or power-hungry. TOPIC combines embedded software, FPGA development and high-performance hardware to distribute processing across the system.

This approach supports high volume data processing and large scale data processing in applications where large sensor or signal streams need to be captured, reduced and processed efficiently.