2 research outputs found
Hardware Accelerated DNA Sequencing
DNA sequencing technology is quickly evolving. The latest developments ex-
ploit nanopore sensing and microelectronics to realize real-time, hand-held devices.
A critical limitation in these portable sequencing machines is the requirement of
powerful data processing consoles, a need incompatible with portability and wide
deployment. This thesis proposes a rst step towards addressing this problem, the
construction of specialized computing modules { hardware accelerators { that can
execute the required computations in real-time, within a small footprint, and at a
fraction of the power needed by conventional computers. Such a hardware accel-
erator, in FPGA form, is introduced and optimized specically for the basecalling
function of the DNA sequencing pipeline. Key basecalling computations are identi-
ed and ported to custom FPGA hardware. Remaining basecalling operations are
maintained in a traditional CPU which maintains constant communications with
its FPGA accelerator over the PCIe bus. Measured results demonstrated a 137X
basecalling speed improvement over CPU-only methods while consuming 17X less
power than a CPU-only method
Embedded CMOS Basecalling for Nanopore DNA Sequencing
DNA sequencing is undergoing a profound evolution into a mobile technology. Unfortunately the effort needed to process the data emerging from this new sequencing technology requires a compute power only available to traditional desktop or cloud-based machines. To empower the full potential of portable DNA solutions a means of efficiently carrying out their computing needs in an embedded format will certainly be required. This thesis presents the design of a custom fixed-point VLSI hardware implementation of an HMM-based multi-channel DNA sequence processor. A 4096 state (6-mer nanopore sensor) basecalling architecture is designed in a 32-nm CMOS technology with the ability to process 1 million DNA base pairs per second per channel. Over a 100 mm^2 silicon footprint the design could process the equivalent of one human genome every 30 seconds at a power consumption of around 5 W