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Description
Coarse Grain Reconfigurable Arrays (CGRAs) are promising accelerators capable of
achieving high performance at low power consumption. While CGRAs can efficiently
accelerate loop kernels, accelerating loops with control flow (loops with if-then-else
structures) is quite challenging. Techniques that handle control flow execution in
CGRAs generally use predication. Such techniques execute both branches of an
if-then-else structure and select outcome of either branch to commit based on the
result of the conditional. This results in poor utilization of CGRA s computational
resources. Dual-issue scheme which is the state of the art technique for control flow
fetches instructions from both paths of the branch and selects one to execute at
runtime based on the result of the conditional. This technique has an overhead in
instruction fetch bandwidth. In this thesis, to improve performance of control flow
execution in CGRAs, I propose a solution in which the result of the conditional
expression that decides the branch outcome is communicated to the instruction fetch
unit to selectively issue instructions from the path taken by the branch at run time.
Experimental results show that my solution can achieve 34.6% better performance
and 52.1% improvement in energy efficiency on an average compared to state of the
art dual issue scheme without imposing any overhead in instruction fetch bandwidth.
achieving high performance at low power consumption. While CGRAs can efficiently
accelerate loop kernels, accelerating loops with control flow (loops with if-then-else
structures) is quite challenging. Techniques that handle control flow execution in
CGRAs generally use predication. Such techniques execute both branches of an
if-then-else structure and select outcome of either branch to commit based on the
result of the conditional. This results in poor utilization of CGRA s computational
resources. Dual-issue scheme which is the state of the art technique for control flow
fetches instructions from both paths of the branch and selects one to execute at
runtime based on the result of the conditional. This technique has an overhead in
instruction fetch bandwidth. In this thesis, to improve performance of control flow
execution in CGRAs, I propose a solution in which the result of the conditional
expression that decides the branch outcome is communicated to the instruction fetch
unit to selectively issue instructions from the path taken by the branch at run time.
Experimental results show that my solution can achieve 34.6% better performance
and 52.1% improvement in energy efficiency on an average compared to state of the
art dual issue scheme without imposing any overhead in instruction fetch bandwidth.
ContributorsRajendran Radhika, Shri Hari (Author) / Shrivastava, Aviral (Thesis advisor) / Christen, Jennifer Blain (Committee member) / Cao, Yu (Committee member) / Arizona State University (Publisher)
Created2014
Description
The manufacturing process for electronic systems involves many players, from chip/board design and fabrication to firmware design and installation.
In today's global supply chain, any of these steps are prone to interference from rogue players, creating a security risk.
Manufactured devices need to be verified to perform only their intended operations since it is not economically feasible to control the supply chain and use only trusted facilities.
It is becoming increasingly necessary to trust but verify the received devices both at production and in the field.
Unauthorized hardware or firmware modifications, known as Trojans,
can steal information, drain the battery, or damage battery-driven embedded systems and lightweight Internet of Things (IoT) devices.
Since Trojans may be triggered in the field at an unknown instance,
it is essential to detect their presence at run-time.
However, it isn't easy to run sophisticated detection algorithms on these devices
due to limited computational power and energy, and in some cases, lack of accessibility.
Since finding a trusted sample is infeasible in general, the proposed technique is based on self-referencing to remove any effect of environmental or device-to-device variations in the frequency domain.
In particular, the self-referencing is achieved by exploiting the band-limited nature of Trojan activity using signal detection theory.
When the device enters the test mode, a predefined test application is run on the device
repetitively for a known period. The periodicity ensures that the spectral electromagnetic power of the test application concentrates at known frequencies, leaving the remaining frequencies within the operating bandwidth at the noise level. Any deviations from the noise level for these unoccupied frequency locations indicate the presence of unknown (unauthorized) activity. Hence, the malicious activity can differentiate without using a golden reference or any knowledge of the Trojan activity attributes.
The proposed technique's effectiveness is demonstrated through experiments with collecting and processing side-channel signals, such as involuntarily electromagnetic emissions and power consumption, of a wearable electronics prototype and commercial system-on-chip under a variety of practical scenarios.
In today's global supply chain, any of these steps are prone to interference from rogue players, creating a security risk.
Manufactured devices need to be verified to perform only their intended operations since it is not economically feasible to control the supply chain and use only trusted facilities.
It is becoming increasingly necessary to trust but verify the received devices both at production and in the field.
Unauthorized hardware or firmware modifications, known as Trojans,
can steal information, drain the battery, or damage battery-driven embedded systems and lightweight Internet of Things (IoT) devices.
Since Trojans may be triggered in the field at an unknown instance,
it is essential to detect their presence at run-time.
However, it isn't easy to run sophisticated detection algorithms on these devices
due to limited computational power and energy, and in some cases, lack of accessibility.
Since finding a trusted sample is infeasible in general, the proposed technique is based on self-referencing to remove any effect of environmental or device-to-device variations in the frequency domain.
In particular, the self-referencing is achieved by exploiting the band-limited nature of Trojan activity using signal detection theory.
When the device enters the test mode, a predefined test application is run on the device
repetitively for a known period. The periodicity ensures that the spectral electromagnetic power of the test application concentrates at known frequencies, leaving the remaining frequencies within the operating bandwidth at the noise level. Any deviations from the noise level for these unoccupied frequency locations indicate the presence of unknown (unauthorized) activity. Hence, the malicious activity can differentiate without using a golden reference or any knowledge of the Trojan activity attributes.
The proposed technique's effectiveness is demonstrated through experiments with collecting and processing side-channel signals, such as involuntarily electromagnetic emissions and power consumption, of a wearable electronics prototype and commercial system-on-chip under a variety of practical scenarios.
ContributorsKarabacak, Fatih (Author) / Ozev, Sule (Thesis advisor) / Ogras, Umit Y. (Thesis advisor) / Christen, Jennifer Blain (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2020