The document discusses HUGenomics, a hardware platform for human genomics. It aims to improve efficiency and scalability for variant discovery and analysis from whole genome sequencing data. Current pure software approaches are inefficient to handle huge amounts of data and computationally intensive algorithms. The document compares different hardware platforms and argues that FPGAs provide good efficiency, reprogrammability, and are well-suited for personalized medicine applications due to their ability to balance costs, accuracy, scale, speed and adaptation capabilities.

1. HUGenomics
Hardware for hUman Genomics
Lorenzo Di Tucci, Giulia Guidi, Chiara Crippa, Marco D. Santambrogio
{giulia.guidi, chiara2.crippa}@mail.polimi.it
{lorenzo.ditucci, marco.santambrogio}@polimi.it
NECST Lab, Politecnico di Milano

2. 2
Variant discovery
https://software.broadinstitute.org

3. 3
Variants
Genetic changes in individuals relative to a reference
genome
• Germ line (inherited)
• Somatic (cancer)
Human Gene)c
Disorders
Personalized
medicine
response to drug treatmentcys4c fibrosis
http://www.ibtimes.co.uk; https://vaultbio.com

4. 4
Workflow
https://software.broadinstitute.org
Pure software
implementation is inefficient
• Huge amount of data
• Computationally intensive
algorithms

5. 5
Platforms overview
Platform CPU ASIC GPU FPGA
Performance
Power
Consumption
Cost
Flexibility
Design

6. 6
FPGA
https://www.xes-inc.com
FPGA
Good efficiency
Reprogrammability

7. 7
FPGAs & Personalized medicine
Biopharmaceu)cal
industries
Reconfigurable
plaCorms
costs
accuracy
scale
speed
adapta4on capabili4es
efficiency
https://www.theresonance.com; https://www.xes-inc.com

8. Thanks for your aRenSon
Follow HUGenomics on:
hRps://www.facebook.com/HUGenomics/
hRps://twiRer.com/HUGgenomics
goo.gl/tli2vq
Lorenzo Di Tucci, Giulia Guidi, Chiara Crippa, Marco D. Santambrogio
{giulia.guidi, chiara2.crippa}@mail.polimi.it
{lorenzo.ditucci, marco.santambrogio}@polimi.it
NECST Lab, Politecnico di Milano