Bancroft: Genomics Acceleration Beyond On-Device Memory
🤖 AI Summary
In computational genomics, limited on-device memory (only 8 GB HBM) impedes efficient random access to terabyte-scale genomic datasets. Method: This paper introduces Bancroft, an FPGA-accelerated platform (Xilinx Alveo U50) that enables PCIe-bandwidth-aware real-time compression/decompression of genomic data. It pioneers fixed-stride Cuckoo hashing for exact-match acceleration and group-header encoding to construct a logically “infinite-capacity” virtual memory abstraction. Memory access is optimized via synergistic HBM/DDR4 co-management. Results: Bancroft achieves 30% of HBM’s peak PCIe bandwidth—10× higher than conventional PCIe-based architectures. For pre-alignment filtering, it delivers 6.2× speedup over baseline, attaining 30% of the peak throughput of HBM-only accelerators and 90% of DDR4-based accelerators.
Application Category
📝 Abstract
This paper presents Bancroft, a computational genomics acceleration platform that provides the illusion of practically infinite on-device memory capacity by compressing genomic data movement over PCIe. Bancroft introduces novel optimizations for efficient accelerator implementation to reference-based genome compression, including fixed-stride matching using cuckoo hashes and grouped header encoding, incorporated into a familiar interface supporting random accesses. We evaluate a prototype implementation of Bancroft on an affordable Alveo U50 FPGA equipped with 8 GB of HBM. Thanks to the orders of magnitude improvements in performance and resource efficiency of genomic compression, our prototype provides access to TBs of host-side genomic data at memory-class performance, measuring speeds over 30% of the on-device HBM bandwidth, an order of magnitude higher than conventional PCIe-limited architectures. Using a real-world pre-alignment filtering application, Bancroft demonstrates over 6x improvement over the conventional PCIe-attached architecture, achieving 30% of peak internal throughput of an accelerator with HBM, and 90% of the one with DDR4. Bancroft supports memory-class performance to practically infinite data capacity, using a small, fixed amount of HBM, making it an attractive solution to continued future scalability of computational genomics.
Problem
Research questions and friction points this paper is trying to address.
Accelerates genomic data processing
Compresses data movement over PCIe
Enhances memory efficiency and performance
Innovation
Methods, ideas, or system contributions that make the work stand out.
Compresses genomic data over PCIe
Uses cuckoo hashes for genome compression
Achieves memory-class performance with HBM
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