Zynq-7000 – The new embedded processing platform

MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
1
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
2
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
3
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
4
Short Profile
Enclustra is a dynamic, innovative and successful FPGA design service company
located in Technopark Zurich, Switzerland.
Our FPGA engineers have in-depth knowledge in various application areas like
software defined radio, drive control, digital signal processing and data acquisition
systems.
Investing in employee training and keeping critical knowledge up to date on a
regular basis enables us to find ideal solutions at a minimal expense for our clients.
We’re vendor-independent, and we’re design service partners of Xilinx®, Altera®
and Lattice Semiconductor – this close communication allows us to be forwardlooking in our design process, and remain on the cutting edge of the most advanced
FPGA technology.
Enclustra – Everything FPGA!
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
5
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
6
Adoption of new Technology
New technology is usually adopted to benefit from its increased capabilities. Even
though there is often some benefit provided by the technology alone, the benefits
can be multiplied by adjusting the methodology to the new technology.
Let’s take the replacement of the good old typewriter by computers as an example.
Certainly there is some benefit from just using the computer: Multiple copies of
documents can be printed and work can be stored in other forms than paper which
is no long-term solution. However, if one still re-types a whole table to just add one
row in the middle (as it was required with a typewriter), big advantages of the new
technology are unused. The same applies for documents which can easily be edited
without re-typing – this was simply not possible in the past.
As a result we changed our methodology. Lists are not growing only at the bottom
end today but are most likely alphabetically sorted and new lines are inserted
somewhere in the middle accordingly. Completely new concepts like the “living
document” which is refined during a whole project popped up and help to improve
our efficiency as well as the quality of results. This nicely shows that the computer
not only has replaced the typewriter in a better way but that we also had to change
the methodology to fully profit from the new features.
On the other hand new technology also rises new problems. Nobody had to care
about anti-virus software for a typewriter.
You are wondering why new technology is emphasized so much? Remember all that
applications where MCUs, DSPs and analog electronics get replaced by FPGAs and
SoCs?
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
7
One possible Way to Rome
According to Freeman Dyson, an Engineer is a person who makes a design that works
with as few original ideas as possible. So you are strongly encouraged to change the
concepts provided to fit your needs, only pick out some ideas or even decide that
the methodology shown does not fit your needs at all. Do not just apply it and
regard it as “the correct way”.
The presentation mainly consists of experiences from real-world FPGA and SoC
projects at Enclustra and things are therefore optimized to the requirements and
processes of Enclustra.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
8
Common Prototyping Problems for FPGA Projects
This section gives an overview over some common problems when prototyping FPGA
projects. This helps understanding why MATLAB based prototypes can be beneficial.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
9
Poor Visibility
One of the main problems when prototyping FPGA projects is the very limited
visibility in the error case, even if the error is perfectly reproducible. For processors
single-stepping through the code and analyzing the content of each variable after
every step is possible and breakpoints can be set. In analog electronics signals can be
measured using a scope. FPGAs don’t provide such kind of an inherent visibility.
There are logic analyzers which can be compiled into the FPGA design to observe
what is happening within the chip. However, these analyzers have very limited
memory and with compile times of hours, routing an additional signal to the logic
analyzer can be quite time consuming.
When the event of failure could be caught using the logic analyzer, data is often not
so easy to interpret since it is not valid all the time, multiple samples are processed in
parallel or data of several channels is mixed up. This is a big contrast to software
debugging where data is often available as array and can be copied away for analysis
easily.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
10
Accessibility
Most specialists for signal processing, control theory or other areas where FPGAs are
commonly used are familiar with software development tools as well as the
programming languages C and C++. For software written in these languages, they
can analyze problems on their own and try different changes in fast iterations.
Unfortunately application specialists are often not familiar with HDL languages and
FPGA tools. Therefore an implementation specialist is required to help capturing data
for analysis and implement changes suggested by the application specialist. This
slows down the development cycle and also introduces more risk for
misunderstandings because of the communication between the application specialist
and the FPGA implementation specialist.
HDL code generation from more accessible languages such as MATLAB/Simulink® or
C can ease this problem. However, code generation is not applicable in many cases
and even if code can be generated, the FPGA tool flow may involve hand-placement
and timing optimization, which again requires effort of the implementation specialist.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
11
Advantages of MATLAB based Prototypes
This section discusses how the impact of the problems mentioned on the last few
slides can be minimized using MATLAB based prototypes.
Note that the concept is not limited to data acquisition systems even though a data
acquisition system is used as example.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
12
MATLAB – The Childhood of Signal Processing Algorithms
MATLAB is a de facto industry standard tool for signal processing algorithm
development. This not only includes the development of the algorithm itself but also
the implementation of stimuli generators as well as functions for result analysis and
plotting. If subsequent processing steps (post-processing) are implemented in other
parts of the system (existing or not) they are often also modelled to judge the overall
system performance.
MATLAB as User Interface
By establishing a connection between the FPGA implementation and MATLAB, all the
data analysis functions and plotting utilities written during algorithm development
can be reused to analyze the performance of the real implementation of the
algorithm and compare it to simulations. While the figure only shows the data flow,
configuration of the processing within the FPGA is also controlled from MATLAB.
The approach shown makes the FPGA design accessible to the signal processing
specialist. He can play with different parameter sets and analyze the output directly
in MATLAB. Compared to the standard flow with a proprietary software to control
the FPGA design and import/export data via Files from/to MATLAB this speeds up
iterations significantly. Another advantage is that parameters such as filter
coefficients can be calculated directly in MATLAB and the design considerations
leading to a given parameter set are therefore inherently traceable.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
13
MATLAB Interface
The easiest way to make the FPGA accessible to an application specialist is to write
FPGA access functions that can be called from normal MATLAB scripts. Usually the
FPGA engineer can write such functions with very little effort since he is aware of all
implementation details. The abstraction level should be chosen in a way to not
expose implementation details to the user of these FPGA access functions.
This approach makes using the actual hardware very similar to just writing a
simulation script as visible from the image on the slide.
Enclustra’s FPGA Manager IP-Solution is a perfect match for the requirements of a
connection between MATLAB and FPGA: It allows configuring the FPGA by doing
register accesses and to receive/transmit streaming data. Its built-in MATLAB
interface further reduces the effort required to access the FPGA from MATLAB. It is
obvious that Enclustra therefore always uses FPGA Manager for MATLAB based
prototyping.
The concept of course also works without FPGA Manager. However, building such a
communication framework from scratch can be quite time consuming.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
14
Flexible Measurement Infrastructure
By providing a flexible measurement infrastructure with several data acquisition
points, many time consuming iterations can be avoided. If results are not as
expected, the singal processing specialist can locate the point of failure by simply
capturing data at several points.
The effect of vaious changes to the algorithm can be tested by capturing data before
the point of failure and execute the rest of the processing (including the proposed
changes) in MATLAB. Again, overall algorithm performance analysis can be done
easily by using the existing infrastructure from simulations. A new FPGA
implementation iteration is only required after the behavior of the changes proposed
was verified using the combination of hardware and MATLAB models shown on the
slide.
The setup shown provides several advantages over a pure simulation:
• All effects caused by the FPGA implementation of all preceeding processing steps
are included
• Real-world data that led to the misbehavior can be captured
• Tests on hardware are possible before the complete algorithm is implemented
• Simulation time can drastically be reduced because parts of the algorithm are
executed in the FPGA at realtime
The last point especially applies if the part of the algorithm executed in the FPGA
contains any form of data rate reduction.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
15
Reproducible Regression Testing
In many projects it is desirable to have a regression testing environment which allows
running the same sets of test data after every change. If the communication between
MATLAB and FPGA is not limited to acquiring data but also allows injecting data,
such regression tests can easily be controlled from MATLAB. In terms of speed, such
a setup outperforms every simulation by factors.
A big advantage of using MATLAB instead of any proprietary software to run such
regression tests is that MATLAB provides a lot of functionality to analyze the output.
This allows analyzing the output in a qualitative way (e.g. statistical analysis,
constellation analysis) which is by far more convienient than a bit-by-bit comparison
to expected output data which will produce many false positives.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
16
Real-World Example
This section proves the usability of MATLAB based prototyping by discussing the
use-cases of a real-world project.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
17
Project Overview
The picture on the slide shows a simplified block diagram of the spectrum analyzer
developed in the project discussed. The large range of configuration values lead to
many cases which cannot reasonably be simulated. Especially high downsampling
ratios together with large FFTs lead to unreasonably long simulation times even for a
single FFT.
Another difficulty is that the application specialist who is responsible for achieving
sufficient overall system performance is employed at the customer and does not
have any FPGA knowledge. Due to simulations not being reasonable, a setup
allowing easy data capturing and analysis without FPGA knowhow must be provided.
Therefore the decision to build a MATLAB based prototype was taken.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
18
Early Perfomance Analysis
Thanks to the MATLAB based prototyping approach, the impact of the down
converter implementation on the performance of the complete system could be
analyzed as soon as the down converter was implemented. For low downsampling
ratios, the performance was known from simulations but for high downsampling
ratios, simulations were not reasonably feasible.
This example nicely shows how a MATLAB based prototype can be used to allow
iterative development. Tests for the down converter performance could be executed
while the FFT was implemented. If any defect was found, it could be fixed early in the
project with little effort.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
19
System Perfomance Analysis
The customer for this project analyzed the system performance in MATLAB. Having
all functions and toolboxes of MATLAB at hand significantly simplified this step.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
20
Debugging
A test data generator was implemented to ensure 100% reproducibility of the input
data that led to a given issue. This concept allowed to reproduce all issues reported
by the customer at Enclustra’s office for finding the root-cause. To track down the
source of any misbehavior quickly, data can be captured at various points in the
design and then analyzed in MATLAB.
A good example for the advantages of this setup is an issue the customer reported in
the early bring-up phase. They reported that the noise level at the output of the
system is higher than expected while the signal-to-noise-ratio (SNR) was still quite
good (70dB instead of 100dB). At these SNR levels the distinction between good and
bad signals cannot be made without a spectral analysis. Fortunately such an analysis
can be implemented in MATLAB easily. Data was then captured at various points in
the design and the component introducing the problem could be identified quickly
by comparing spectrums of input and output.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
21
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
22
Risk Reduction
The approach of MATLAB based prototyping significantly reduces development risk.
It allows early testing of critical entities on the hardware by the application specialist.
This greatly reduces the risk of finding problems with the system performance late in
the project where changes can be very costly. The accessibility of the system to the
application specialist is very important since this prevents misunderstandings
between application and implementation specialist from not being detected until
late in the project.
The availability of all the algorithms and toolboxes MATLAB provides leads to more
thorough testing.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
23
Time Savings
MATLAB based prototypes save a lot of time during the bring-up and debug phase
of a project. They not only lead to faster identification of root causes for problems
but also help reducing the number of iterations required to fix issues. Since those
iterations are quite time consuming for FPGA/SoC projects with their long compile
times, this is a very important advantage.
FPGA/SoC projects are also well known for their long simulation times. By running
tests on hardware and only analyzing results in MATLAB, regression tests times can
be significantly reduced.
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
24
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com
MATLAB® based Prototyping of FPGA Projects
Embedded Computing Conference 2016
ZHAW Winterthur, May 31, 2016
25
Enclustra GmbH
Technoparkstr. 1 – CH-8005 Zürich – Switzerland
Phone +41 43 343 39 43 – www.enclustra.com