1 research outputs found
Dynamic partial reconfiguration management for high performance and reliability in FPGAs
Modern Field-Programmable Gate Arrays (FPGAs) are no longer used to implement
small “glue logic” circuitries. The high-density of reconfigurable logic resources in
today’s FPGAs enable the implementation of large systems in a single chip. FPGAs
are highly flexible devices; their functionality can be altered by simply loading a new
binary file in their configuration memory. While the flexibility of FPGAs is
comparable to General-Purpose Processors (GPPs), in the sense that different
functions can be performed using the same hardware, the performance gain that can
be achieved using FPGAs can be orders of magnitudes higher as FPGAs offer the
ability for customisation of parallel computational architectures.
Dynamic Partial Reconfiguration (DPR) allows for changing the functionality of
certain blocks on the chip while the rest of the FPGA is operational. DPR has
sparked the interest of researchers to explore new computational platforms where
computational tasks are off-loaded from a main CPU to be executed using dedicated
reconfigurable hardware accelerators configured on demand at run-time. By having a
battery of custom accelerators which can be swapped in and out of the FPGA at runtime,
a higher computational density can be achieved compared to static systems
where the accelerators are bound to fixed locations within the chip. Furthermore, the
ability of relocating these accelerators across several locations on the chip allows for
the implementation of adaptive systems which can mitigate emerging faults in the
FPGA chip when operating in harsh environments. By porting the appropriate fault
mitigation techniques in such computational platforms, the advantages of FPGAs can
be harnessed in different applications in space and military electronics where FPGAs
are usually seen as unreliable devices due to their sensitivity to radiation and extreme
environmental conditions.
In light of the above, this thesis investigates the deployment of DPR as: 1) a method
for enhancing performance by efficient exploitation of the FPGA resources, and 2) a
method for enhancing the reliability of systems intended to operate in harsh
environments. Achieving optimal performance in such systems requires an efficient
internal configuration management system to manage the reconfiguration and
execution of the reconfigurable modules in the FPGA. In addition, the system needs
to support “fault-resilience” features by integrating parameterisable fault detection
and recovery capabilities to meet the reliability standard of fault-tolerant
applications. This thesis addresses all the design and implementation aspects of an
Internal Configuration Manger (ICM) which supports a novel bitstream relocation
model to enable the placement of relocatable accelerators across several locations on
the FPGA chip. In addition to supporting all the configuration capabilities required to
implement a Reconfigurable Operating System (ROS), the proposed ICM also
supports the novel multiple-clone configuration technique which allows for cloning
several instances of the same hardware accelerator at the same time resulting in much
shorter configuration time compared to traditional configuration techniques. A faulttolerant
(FT) version of the proposed ICM which supports a comprehensive faultrecovery
scheme is also introduced in this thesis. The proposed FT-ICM is designed
with a much smaller area footprint compared to Triple Modular Redundancy (TMR)
hardening techniques while keeping a comparable level of fault-resilience.
The capabilities of the proposed ICM system are demonstrated with two novel
applications. The first application demonstrates a proof-of-concept reliable FPGA
server solution used for executing encryption/decryption queries. The proposed
server deploys bitstream relocation and modular redundancy to mitigate both
permanent and transient faults in the device. It also deploys a novel Built-In Self-
Test (BIST) diagnosis scheme, specifically designed to detect emerging permanent
faults in the system at run-time. The second application is a data mining application
where DPR is used to increase the computational density of a system used to
implement the Frequent Itemset Mining (FIM) problem