3,767 research outputs found
Resource Optimized Quantum Architectures for Surface Code Implementations of Magic-State Distillation
Quantum computers capable of solving classically intractable problems are
under construction, and intermediate-scale devices are approaching completion.
Current efforts to design large-scale devices require allocating immense
resources to error correction, with the majority dedicated to the production of
high-fidelity ancillary states known as magic-states. Leading techniques focus
on dedicating a large, contiguous region of the processor as a single
"magic-state distillation factory" responsible for meeting the magic-state
demands of applications. In this work we design and analyze a set of optimized
factory architectural layouts that divide a single factory into spatially
distributed factories located throughout the processor. We find that
distributed factory architectures minimize the space-time volume overhead
imposed by distillation. Additionally, we find that the number of distributed
components in each optimal configuration is sensitive to application
characteristics and underlying physical device error rates. More specifically,
we find that the rate at which T-gates are demanded by an application has a
significant impact on the optimal distillation architecture. We develop an
optimization procedure that discovers the optimal number of factory
distillation rounds and number of output magic states per factory, as well as
an overall system architecture that interacts with the factories. This yields
between a 10x and 20x resource reduction compared to commonly accepted single
factory designs. Performance is analyzed across representative application
classes such as quantum simulation and quantum chemistry.Comment: 16 pages, 14 figure
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Nanometer VLSI placement and optimization for multi-objective design closure
In a VLSI physical synthesis flow, placement directly defines the interconnection,
which affects many other design objectives, such as timing, power consumption,
congestion, and thermal issues. With the scaling of technology, the relative interconnect
delay increases dramatically. As a result, placement has become a bottleneck
in deep sub-micron physical synthesis. In this dissertation, I propose several
optimization algorithms from global placement, placement migration, timing driven
placements, to incremental power optimizations for multi-objective VLSI design
closure. The first work is DPlace, a new global placement algorithm that scales
well to the modern large-scale circuit placement problems. DPlace simulates the
natural diffusion process to spread cells smoothly over the placement region, and
uses both analytical and discrete techniques to improve the wire length. However,
global placement is never sufficient for multi-objective design closure, a variety of
design objectives have to be improved incrementally, such as timing, routing congestion,
signal integrity, and heat distribution. Placement migration is a critical step
to address the cell overlaps appearing during incremental optimizations. To achieve
high placement stability, I propose a computational geometry based placement migration
flow to cope with placement changes, and a new stability metric to measure
the “similarity” between two placements accurately. Our placement migration algorithm
has clear advantage over conventional legalization algorithms such that the
neighborhood characteristics of the original placement are preserved. For timing
closure in high performance designs, I present a linear programming based incremental
timing driven placement to improve the timing on critical paths directly.
I further present an efficient timing driven placement algorithm (Pyramids). Two
formulations of Pyramids are proposed, which are suitable for different optimization
stages in a physical synthesis flow. Both approaches find the optimal location
for timing of a cell in constant time, through computational geometry based approaches.
For fast convergence of design closure, placement should be integrated
with other optimization techniques. I propose to combine placement, gate sizing
and Vt swapping techniques to reduce the total power consumption, especially the
leakage power, which is becoming increasingly critical for nanometer VLSI design
closure.Electrical and Computer Engineerin
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