The document discusses using FPGAs to accelerate bioinformatics algorithms. It describes how increasing data sizes and algorithm complexity have led to high computational needs that hardware accelerators can help address through parallelism and low power consumption. It presents work done to accelerate the Smith-Waterman and protein folding algorithms on FPGAs. It proposes the HUG system to provide advanced support for personalized medicine research through efficient algorithm execution, bioinformatics support, and efficient visualization. Future work includes integrating new visualization methods and using multiple FPGAs through AWS F1 instances.

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FPGA-enhanced Bioinformatics
@NECST
06/08/2017
Xilinx, San Jose, CA
Lorenzo Di Tucci & co.
lorenzo.ditucci@polimi.it
NECST Lab, Politecnico di Milano

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Problem
Performance requirements of biological algorithms increased as..

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Problem
Performance requirements of biological algorithms increased as..
Large amount of data

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Problem
Performance requirements of biological algorithms increased as..
Large amount of data

5. 2
Problem
Performance requirements of biological algorithms increased as..
Large amount of data Algorithm complexity

6. 2
Problem
Performance requirements of biological algorithms increased as..
Large amount of data Algorithm complexity
HIGH
COMPUTATIONAL
NEEDS

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Hardware solution
In such scenario, hardware accelerators proved to be effective
in optimizing the Performance/Power Consumption ratio

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Hardware solution
In such scenario, hardware accelerators proved to be effective
in optimizing the Performance/Power Consumption ratio
High parallelism

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Hardware solution
In such scenario, hardware accelerators proved to be effective
in optimizing the Performance/Power Consumption ratio
High parallelism Low power consumption

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Traditional medicine

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Traditional medicine

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Traditional medicine

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Personalized medicine

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Personalized medicine

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Personalized medicine

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Personalized medicine

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Issues

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Issues
Further biological research is needed

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Issues
Further biological research is needed
Each individual DNA provides huge amount of data

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Issues
Further biological research is needed
Each individual DNA provides huge amount of data
To produce a tailor-made drug, for each DNA:

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Issues
Further biological research is needed
Each individual DNA provides huge amount of data
To produce a tailor-made drug, for each DNA:

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Issues
Further biological research is needed
Each individual DNA provides huge amount of data
To produce a tailor-made drug, for each DNA:

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Issues
Further biological research is needed
Each individual DNA provides huge amount of data
To produce a tailor-made drug, for each DNA:

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Issues
Further biological research is needed
Each individual DNA provides huge amount of data
To produce a tailor-made drug, for each DNA:

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Issues

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Issues

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Issues

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Issues

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Issues

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Issues

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Issues

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Issues

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Issues

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Issues

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Issues

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Proposed solution

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Proposed solution
Advanced support for
bioinformatics

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Proposed solution
Efficient algorithm
execution
Advanced support for
bioinformatics

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Proposed solution

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Proposed solution

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Proposed solution

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Proposed solution

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Proposed solution

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Implementation

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Implementation

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Implementation

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Implementation

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Proposed solution
Heterogeneity of competences to create efficient data visualization,
focusing on biological meanings

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Proposed solution
Efficient algorithm
execution
Advanced support for
bioinformatics

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Proposed solution
Efficient algorithm
execution
Advanced support for
bioinformatics
Efficient visualization
of results

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Proposed solution

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Timeline

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Timeline
Nov 2015
HP implementation of Smith-Waterman algorithm

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Smith-Waterman
• Dynamic programming algorithm
• Perform local sequence alignment between two nucleotides or protein
• Guaranteed to find the optimal local alignment with regards to the scoring
system used

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Smith-Waterman
• Dynamic programming algorithm
• Perform local sequence alignment between two nucleotides or protein
• Guaranteed to find the optimal local alignment with regards to the scoring
system used
• Highly compute intensive

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Smith-Waterman
• Dynamic programming algorithm
• Perform local sequence alignment between two nucleotides or protein
• Guaranteed to find the optimal local alignment with regards to the scoring
system used
• In order to increase system performance, the state of the art is full of
implementation based on heuristics
• Highly compute intensive

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Smith-Waterman
• Dynamic programming algorithm
• Perform local sequence alignment between two nucleotides or protein
• Guaranteed to find the optimal local alignment with regards to the scoring
system used
• In order to increase system performance, the state of the art is full of
implementation based on heuristics
• Highly compute intensive
Speedup
in computation

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Smith-Waterman
• Dynamic programming algorithm
• Perform local sequence alignment between two nucleotides or protein
• Guaranteed to find the optimal local alignment with regards to the scoring
system used
• In order to increase system performance, the state of the art is full of
implementation based on heuristics
• Highly compute intensive
Speedup
in computation
Decrease in algorithm
precision

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Smith-Waterman
Platform Performance
[GCUPS]
Power Efficiency
[GCUPS/Watt]
ADM-PCIE-KU3 42.5 1.699
Altera Stratix V on Nallatech
PCIe-385
24.7 0.988
ADM-PCIE-7V3 14.8 0.594
Xtreme Data XD1000 25.6 0.430
Tesla K20 45.0 0.200
Xtreme Data XD2000i 9.00 0.150
Nvidia GeForce GTX 295 30.0 0.104
Dual-core Nvidia 9800 GX2 14.5 0.074
Nvidia GeForce GTX 295 16.1 0.056
Nvidia GeForce GTX 280 9.66 0.0041
2XNvidia GeForce 8800 3.60 0.017
Di Tucci, Lorenzo, Kenneth O'Brien, Michaela Blott, and Marco D. Santambrogio. "Architectural optimizations for high performance and energy efficient Smith-
Waterman implementation on FPGAs using OpenCL." In 2017 Design, Automation & Test in Europe Conference & Exhibition (DATE), pp. 716-721. IEEE, 2017.

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Timeline
Nov 2015
Hardware acceleration of a protein folding algorithm
Mar 2016

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ProFAX
• Ab Initio modeling creates the 3D-structure from energetic
and geometrical features
ProFAX is a hardware acceleration of an Ab Initio Protein Folding
algorithm based on Monte Carlo Simulation (MCS)
Monte Carlo methodology:
• series of random steps in conformation space, each perturbing some
degrees of freedom of the molecule
• step is accepted with a probability, depending on an energy function

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ProFAX
Giulia Guidi, Lorenzo Di Tucci, and Marco D. Santambrogio. "ProFAX: A hardware acceleration of a protein folding algorithm." In Research and Technologies
for Society and Industry Leveraging a better tomorrow (RTSI), 2016 IEEE 2nd International Forum on, pp. 1-6. IEEE, 2016.

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Timeline
Mar 2016Nov 2015 TODAY

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Preliminary analysis

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Preliminary analysis

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Preliminary analysis

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Roofline model
Performance model that depicts the relation between attainable
performance and operational intensity

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Roofline models for FPGA
• Estimate performance before implementing the kernel
• Compare performance on different FPGA boards
• FPGAs have no fixed architecture
- It needs to be generated for each kernel
- and each target FPGA board

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Roofline models for FPGA
• Estimate performance before implementing the kernel
• Compare performance on different FPGA boards
• FPGAs have no fixed architecture
- It needs to be generated for each kernel
- and each target FPGA board
Proposed solution: automatic tool to generate Roofline models

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Rationale
Maximum performance are kernel and FPGA specific
• Maximum performance of a kernel are obtained once
- Code is fully optimized
- The FPGA provides sufficient resources

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Ceilings & Walls
Original Roofline
• ceiling represents optimizations
• The performance won’t increase
if the ceiling is not reached
Roofline for FPGA
• Ceilings are HLS optimizations
• Walls represents O.I.
optimizations

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Optimization Flow
• Intersection points between walls and ceilings represent possible HW implementations
•Navigate through the graph moving towards high performance solutions
• All generated points must be solutions not exceeding FPGA resource budget (legal
points)

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Automatic DSE
• Generation of legal point done automatically
- Start from initial source code, considers optimizations to generate
new points
• Space Exploration can be done automatically
- Taken a set of valid points, the tool calculates the set of
transformations to be performed to get the best performance
• Combining the two aspects
- Automatic DSE for High Level Synthesis on FPGAs

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SDAccel
• Based on the Vivado Design Suite
• Given High Level Code, it generates bitstream for the target board
• Resembles GPU design flow

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SDAccel
• Based on the Vivado Design Suite
• Given High Level Code, it generates bitstream for the target board
• Resembles GPU design flow
Host
OpenCL runtime & APIs

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SDAccel
• Based on the Vivado Design Suite
• Given High Level Code, it generates bitstream for the target board
• Resembles GPU design flow
Host
OpenCL runtime & APIs
Accelerator
C, C++, OpenCL
PCIe

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The Future: Timeline
As of now, multiple applications are being integrated
Nov 2015 Mar 2016

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Conclusions and Future Works
We presented
• HUG: a hardware/software systems that aims at becoming an
advanced support for the research for personalized medicine
• Roofline for FPGAs: an automatic tool for generating application
& target specific rooflines

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Conclusions and Future Works
We presented
• HUG: a hardware/software systems that aims at becoming an
advanced support for the research for personalized medicine
• Roofline for FPGAs: an automatic tool for generating application
& target specific rooflines
Future Works

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Conclusions and Future Works
• Research & Integrations of new visualization
methodologies
We presented
• HUG: a hardware/software systems that aims at becoming an
advanced support for the research for personalized medicine
• Roofline for FPGAs: an automatic tool for generating application
& target specific rooflines
Future Works

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Conclusions and Future Works
• Research & Integrations of new visualization
methodologies
•Integration of AWS F1 instances to exploit multi-FPGA
We presented
• HUG: a hardware/software systems that aims at becoming an
advanced support for the research for personalized medicine
• Roofline for FPGAs: an automatic tool for generating application
& target specific rooflines
Future Works

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Thanks for your attention
Questions?
Lorenzo Di Tucci & co.
lorenzo.ditucci@polimi.it
NECST Lab, Politecnico di Milano