6,854 research outputs found
Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations
Although double-precision floating-point arithmetic currently dominates
high-performance computing, there is increasing interest in smaller and simpler
arithmetic types. The main reasons are potential improvements in energy
efficiency and memory footprint and bandwidth. However, simply switching to
lower-precision types typically results in increased numerical errors. We
investigate approaches to improving the accuracy of reduced-precision
fixed-point arithmetic types, using examples in an important domain for
numerical computation in neuroscience: the solution of Ordinary Differential
Equations (ODEs). The Izhikevich neuron model is used to demonstrate that
rounding has an important role in producing accurate spike timings from
explicit ODE solution algorithms. In particular, fixed-point arithmetic with
stochastic rounding consistently results in smaller errors compared to single
precision floating-point and fixed-point arithmetic with round-to-nearest
across a range of neuron behaviours and ODE solvers. A computationally much
cheaper alternative is also investigated, inspired by the concept of dither
that is a widely understood mechanism for providing resolution below the least
significant bit (LSB) in digital signal processing. These results will have
implications for the solution of ODEs in other subject areas, and should also
be directly relevant to the huge range of practical problems that are
represented by Partial Differential Equations (PDEs).Comment: Submitted to Philosophical Transactions of the Royal Society
Performance evaluation of an open distributed platform for realistic traffic generation
Network researchers have dedicated a notable part of their efforts
to the area of modeling traffic and to the implementation of efficient traffic
generators. We feel that there is a strong demand for traffic generators
capable to reproduce realistic traffic patterns according to theoretical
models and at the same time with high performance. This work presents an open
distributed platform for traffic generation that we called distributed
internet traffic generator (D-ITG), capable of producing traffic (network,
transport and application layer) at packet level and of accurately replicating
appropriate stochastic processes for both inter departure time (IDT) and
packet size (PS) random variables. We implemented two different versions of
our distributed generator. In the first one, a log server is in charge of
recording the information transmitted by senders and receivers and these
communications are based either on TCP or UDP. In the other one, senders and
receivers make use of the MPI library. In this work a complete performance
comparison among the centralized version and the two distributed versions of
D-ITG is presented
Magic State Distillation with Low Space Overhead and Optimal Asymptotic Input Count
We present an infinite family of protocols to distill magic states for
-gates that has a low space overhead and uses an asymptotic number of input
magic states to achieve a given target error that is conjectured to be optimal.
The space overhead, defined as the ratio between the physical qubits to the
number of output magic states, is asymptotically constant, while both the
number of input magic states used per output state and the -gate depth of
the circuit scale linearly in the logarithm of the target error (up to
). Unlike other distillation protocols, this protocol
achieves this performance without concatenation and the input magic states are
injected at various steps in the circuit rather than all at the start of the
circuit. The protocol can be modified to distill magic states for other gates
at the third level of the Clifford hierarchy, with the same asymptotic
performance. The protocol relies on the construction of weakly self-dual CSS
codes with many logical qubits and large distance, allowing us to implement
control-SWAPs on multiple qubits. We call this code the "inner code". The
control-SWAPs are then used to measure properties of the magic state and detect
errors, using another code that we call the "outer code". Alternatively, we use
weakly-self dual CSS codes which implement controlled Hadamards for the inner
code, reducing circuit depth. We present several specific small examples of
this protocol.Comment: 39 pages, (v2) renamed "odd" and "even" weakly self-dual CSS codes of
(v1) to "normal" and "hyperbolic" codes, respectively. (v3) published in
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