3 research outputs found
Addressing Resiliency of In-Memory Floating Point Computation
In-memory computing (IMC) can eliminate the data movement between processor
and memory which is a barrier to the energy-efficiency and performance in
Von-Neumann computing. Resistive RAM (RRAM) is one of the promising devices for
IMC applications (e.g. integer and Floating Point (FP) operations and random
logic implementation) due to low power consumption, fast operation, and small
footprint in crossbar architecture. In this paper, we propose FAME, a pipelined
FP arithmetic (adder/subtractor) using RRAM crossbar based IMC. A novel shift
circuitry is proposed to lower the shift overhead during FP operations. Since
96% of the RRAMs used in our architecture are in High Resistance State (HRS),
we propose two approaches namely Shift-At-The-Output (SATO) and Force To VDD
(FTV) (ground (FTG)) to mitigate Stuck-at-1 (SA1) failures. In both techniques,
the fault-free RRAMs are exploited to perform the computation by using an extra
clock cycle. Although performance degrades by 50%, SATO can handle 50% of the
faults whereas FTV can handle 99% of the faults in the RRAM-based compute array
at low power and area overhead. Simulation results show that the proposed
single precision FP adder consumes 335 pJ and 322 pJ for NAND-NAND and NOR-NOR
based implementations, respectively. The area overheads of SATO and FTV are
28.5% and 9.5%, respectively
SCARE: Side Channel Attack on In-Memory Computing for Reverse Engineering
In-memory computing architectures provide a much needed solution to
energy-efficiency barriers posed by Von-Neumann computing due to the movement
of data between the processor and the memory. Functions implemented in such
in-memory architectures are often proprietary and constitute confidential
Intellectual Property. Our studies indicate that IMCs implemented using RRAM
are susceptible to Side Channel Attack. Unlike conventional SCAs that are aimed
to leak private keys from cryptographic implementations, SCARE can reveal the
sensitive IP implemented within the memory. Therefore, the adversary does not
need to perform invasive Reverse Engineering to unlock the functionality. We
demonstrate SCARE by taking recent IMC architectures such as DCIM and MAGIC as
test cases. Simulation results indicate that AND, OR, and NOR gates (building
blocks of complex functions) yield distinct power and timing signatures based
on the number of inputs making them vulnerable to SCA. Although process
variations can obfuscate the signatures due to significant overlap, we show
that the adversary can use statistical modeling and analysis to identify the
structure of the implemented function. SCARE can find the implemented IP by
testing a limited number of patterns. For example, the proposed technique
reduces the number of patterns by 64% compared to a brute force attack for a+bc
function. Additionally, analysis shows improvement in SCAREs detection model
due to adversarial change in supply voltage for both DCIM and MAGIC. We also
propose countermeasures such as redundant inputs and expansion of literals.
Redundant inputs can mask the IP with 25% area and 20% power overhead. However,
functions can be found by greater RE effort. Expansion of literals incurs 36%
power overhead. However, it imposes brute force search by the adversary for
which the RE effort increases by 3.04X
Reservoir Computing using High Order Synchronization of Coupled Oscillators
We propose a concept for reservoir computing on oscillators using the
high-order synchronization effect. The reservoir output is presented in the
form of oscillator synchronization metrics: fractional high-order
synchronization value and synchronization efficiency, expressed as a
percentage. Using two coupled relaxation oscillators built on VO2 switches, we
created an oscillator reservoir that allows simulating the XOR operation. The
reservoir can operate as with static input data (power currents, coupling
forces), as with dynamic data in the form of spike sequences. Having a small
number of oscillators and significant non-linearity, the reservoir expresses a
wide range of dynamic states. The proposed computing concept can be implemented
on oscillators of diverse nature.Comment: 8 pages, 7 figure