Breaking Search Performance Limits with Domain-Specific Computing

The demand for advanced search is higher than ever: organization data is growing exponentially, while millions to billions of documents are becoming standard and the search queries become more resource-intensive, leading to longer query times and higher latency.

Yet, it is becoming extremely difficult to achieve search at scale due to cloud computing costs, software limits, and real-time requirements. Furthermore, general purpose CPUs are limited in processing power and parallelism, especially when dealing with complex algorithms such as TF/IDF, k/ANN, etc. which makes it nearly impossible to reach consistent real-time latencies of under 100ms.

To solve this, a new approach is to program a dedicated chip, based on cloud FPGAs, which is highly parallelizable and designed for high-throughput / low latency search workloads. This technologic step function breaks today’s limits and allow latencies that are 100x faster, at billion-scale, and at a fraction of existing hardware costs.

Ohad Levi

Hyperspace

Co-founder and CEO of Hyperspace, product leader and entrepreneur. Passionate about data, search and performance and specialized in building best-in-class products in the conjunction between data, AI and algorithm optimization. Now started Hyperspace to solve some of the most challenging search performance, scalability and cost issues, breaking the limits of real-time search.