BittWare Partner IP
NoLoad® Query Engine
Build FPGA-powered accelerators to query, analyze or reformat stored or streaming data at PCIe Gen4 speeds!
Eideticom’s Query Engine targets database users or anyone streaming data (such as network packets) who need query, analytics or format conversion done in hardware with low latency. Tasks can be parallelized to meet any bandwidth needs, plus mixed with other NoLoad® functions like compression.
Built on the NoLoad® Framework
As part of Eideticom’s NoLoad computational storage framework, the Query Engine can be pipelined with other Computational Storage IP from Eideticom such as Compression, Decompression Erasure Coding and Deduplication.
Software-Driven Design
Relieving the burden of hardware engineers being involved in specifying the Query Engine parameters, users define the functions using an on-chip processor. This gives both high-level tool ease-of-use and offload from the main host CPU.
The Query Engine includes features for format conversion (text to/from binary) or standards-driven database functions. Users design their mix of functions in software—no hardware-based tools are necessary. The Engine will support native acceleration for a range of database tools as these packages move to support standards-based computational storage.
Query
Analyze
Reformat
Software Defined + Scalable for Your Bandwidth Requirements
The Query Engine is defined in software that runs on the FPGA (using soft or hard processor), eliminating the need for low-level configuration engineering resources.
The Query Engine is modular, allowing for one or more engines to be placed to meet a certain bandwidth requirements. Engine instances can cooperate, for example with a distributed file conversion over eight Query Engines where data spanning two engines needs to be coordinated.
How Query Engine Works Inside of NoLoad®, Deployed on BittWare’s IA-220-U2 Module or IA-420F Card
Built on the NoLoad® Computational Storage Framework from Eideticom
Query Engine is a component of the NoLoad framework. The components such as Compression in orange are where users build their particular application using a software-defined approach.
Components like Compression can be added to the Query engine to, for example, compress filtered data before moving to SSD storage.
All the accelerator functions shown are implemented in FPGA hardware, allowing for high bandwidth, low latency and CPU offload.
Use Case
Capture + Analytics Engine for Fintech
Building a High-performance, Software-defined Packet Capture and Analytics Engine
Performance Advantage
Compared to a multi-threaded Intel Xeon CPU, the database query engine performs as show below.| Avg. Packet Size | CPU | 1× Query Engine (QE) | 2× QE | 4× QE |
|---|---|---|---|---|
| 256B | 0.2 GB/s | 1.8 GB/s | 3.6 GB/s | 7.2 GB/s |
| 1024B | 0.7 GB/s | 2.0 GB/s | 4.0 GB/s | 8.0 GB/s |
| 4096B | 1.9 GB/s | 2.0 GB/s | 4.0 GB/s | 8.0 GB/s |
| 9216B | 2.7 GB/s | 2.0 GB/s | 4.0 GB/s | 8.0 GB/s |
Use Case
Database Query Acceleration
Accelerate Database Queries and More
In a database acceleration configuration, the Query Engine can perform a range of functions from CPU offload to data type format conversions.
- Implements CSV/JSON/Parquet parsing and query execution
- 70-80% Improved CPU Offload with 5-10× Increased Performance
- Deployment flexibility in compute, storage and cloud
- NVMe driver achieves low latency high throughput data transfers
- NoLoad Query Engine can be paired with NoLoad compression and decompression engines
Compatible FPGA Cards
Query Engine targets BittWare’s cards with Intel Agilex FPGAs.
Interested in Pricing or More Information?
Our technical sales team is ready to provide availability and configuration information, or answer your technical questions.
