2,562,032 research outputs found
Singleton-Optimal LRCs and Perfect LRCs via Cyclic and Constacyclic Codes
Locally repairable codes (LRCs) have emerged as an important coding scheme in
distributed storage systems (DSSs) with relatively low repair cost by accessing
fewer non-failure nodes. Theoretical bounds and optimal constructions of LRCs
have been widely investigated. Optimal LRCs via cyclic and constacyclic codes
provide significant benefit of elegant algebraic structure and efficient
encoding procedure. In this paper, we continue to consider the constructions of
optimal LRCs via cyclic and constacyclic codes with long code length.
Specifically, we first obtain two classes of -ary cyclic Singleton-optimal
-LRCs with length when and is
even, and length when and , respectively. To the best of our knowledge, this is the first
construction of -ary cyclic Singleton-optimal LRCs with length and
minimum distance . On the other hand, an LRC acheiving the
Hamming-type bound is called a perfect LRC. By using cyclic and constacyclic
codes, we construct two new families of -ary perfect LRCs with length
, minimum distance and locality
Significant Conditions on the Two-electron Reduced Density Matrix from the Constructive Solution of N-representability
We recently presented a constructive solution to the N-representability
problem of the two-electron reduced density matrix (2-RDM)---a systematic
approach to constructing complete conditions to ensure that the 2-RDM
represents a realistic N-electron quantum system [D. A. Mazziotti, Phys. Rev.
Lett. 108, 263002 (2012)]. In this paper we provide additional details and
derive further N-representability conditions on the 2-RDM that follow from the
constructive solution. The resulting conditions can be classified into a
hierarchy of constraints, known as the (2,q)-positivity conditions where the q
indicates their derivation from the nonnegativity of q-body operators. In
addition to the known T1 and T2 conditions, we derive a new class of
(2,3)-positivity conditions. We also derive 3 classes of (2,4)-positivity
conditions, 6 classes of (2,5)-positivity conditions, and 24 classes of
(2,6)-positivity conditions. The constraints obtained can be divided into two
general types: (i) lifting conditions, that is conditions which arise from
lifting lower (2,q)-positivity conditions to higher (2,q+1)-positivity
conditions and (ii) pure conditions, that is conditions which cannot be derived
from a simple lifting of the lower conditions. All of the lifting conditions
and the pure (2,q)-positivity conditions for q>3 require tensor decompositions
of the coefficients in the model Hamiltonians. Subsets of the new
N-representability conditions can be employed with the previously known
conditions to achieve polynomially scaling calculations of ground-state
energies and 2-RDMs of many-electron quantum systems even in the presence of
strong electron correlation
Extensive nonadditive entropy in quantum spin chains
We present details on a physical realization, in a many-body Hamiltonian
system, of the abstract probabilistic structure recently exhibited by
Gell-Mann, Sato and one of us (C.T.), that the nonadditive entropy ( density matrix; ) can conform, for an anomalous value of q (i.e., q
not equal to 1), to the classical thermodynamical requirement for the entropy
to be extensive. Moreover, we find that the entropic index q provides a tool to
characterize both universal and nonuniversal aspects in quantum phase
transitions (e.g., for a L-sized block of the Ising ferromagnetic chain at its
T=0 critical transverse field, we obtain
). The present results
suggest a new and powerful approach to measure entanglement in quantum
many-body systems. At the light of these results, and similar ones for a d=2
Bosonic system discussed by us elsewhere, we conjecture that, for blocks of
linear size L of a large class of Fermionic and Bosonic d-dimensional many-body
Hamiltonians with short-range interaction at T=0, we have that the additive
entropy (i.e., for , and for d>1), hence it is not extensive, whereas, for anomalous values of
the index q, we have that the nonadditive entropy (), i.e., it is extensive. The present discussion neatly illustrates that
entropic additivity and entropic extensivity are quite different properties,
even if they essentially coincide in the presence of short-range correlations.Comment: 9 pages, 4 figures, Invited Paper presented at the international
conference CTNEXT07, satellite of STATPHYS23, 1-5 July 2007, Catania, Ital
Why is the CMB fluctuation level 10^{-5}?
We explore the qualitative changes that would occur if the amplitude Q ~
10^{-5} of cosmological density fluctuations were different. If is less than
about 10^{-6}, the cosmological objects that form would have so low virial
temperatures that they may be unable to cool and form stars, and would be so
loosely bound that even if they could produce a supernova explosion, they might
be unable to retain the heavy elements necessary for planetary life. If Q is
greater than about 10^{-4}, dense supermassive galaxies would form, and
biological evolution could be marred by short disruption timescales for
planetary orbits. If Q were still larger, most bound systems would collapse
directly to supermassive black holes. These constraints on Q can be expressed
in terms of fundamental constants alone, and depend only on the electromagnetic
and gravitational coupling constants, the electron-proton mass ratio and the
matter-to-photon ratio. We discuss the implications for inflation and defect
models, and note that the recent anthropic upper bounds on the cosmological
constant Lambda would be invalid if both Q and Lambda could vary and there were
no anthropic constraints on Q. The same applies to anthropic bounds on the
curvature parameter Omega.Comment: Revised to match accepted version. 8 pages, with 1 figure included.
Color figure and related links at http://www.sns.ias.edu/~max/Q.html (faster
from the US), from http://www.mpa-garching.mpg.de/~max/Q.html (faster from
Europe) or from [email protected]. ApJ, in pres
P-q theory power components calculations
The โGeneralized theory of the instantaneous reactive power in three-phase circuits", proposed by Akagi et al., and also known as the p-q theory, is an interesting tool to apply to the control of active power filters, or even to analyze three-phase power systems in order to detect problems related to harmonics, reactive power and unbalance.
In this paper it will be shown that in three phase electrical systems the instantaneous power waveform presents symme-tries of 1/6, 1/3, 1/2 or 1 cycle of the power system fundamen-tal frequency, depending on the system being balanced or not, and having or not even harmonics (interharmonics and sub-harmonics are not considered in this analysis). These symme-tries can be exploited to accelerate the calculations for active filters controllers based on the p-q theory. In the case of the conventional reactive power or zero-sequence compensation, it is shown that the theoretical control system dynamic response delay is zero.Fundaรงรฃo para a Ciรชncia e a Tecnologia (FCT) - POCTI/ESE/41170/2001
Chiral heavy fermions in a two Higgs doublet model: 750 GeV resonance or not
We revisit models where a heavy chiral 4th generation doublet of fermions is
embedded in a class of two Higgs doublets models (2HDM) with a discrete
symmetry, which couples the "heavy" scalar doublet only to the 4th generation
fermions and the "light" one to the Standard Model (SM) fermions - the
so-called 4G2HDM introduced by us several years ago. We study the constraints
imposed on the 4G2HDM from direct searches of heavy fermions, from precision
electroweak data (PEWD) and from the measured production and decay signals of
the 125 GeV scalar, which in the 4G2HDM corresponds to the lightest CP-even
scalar h. We then show that the recently reported excess in the
spectrum around 750 GeV can be accommodated by the heavy CP-even scalar of the
4G2HDM, H, resulting in a unique choice of parameter space: negligible mixing
(sin\alpha ~ O(0.001)) between the two CP-even scalars h,H and heavy 4th
generation quark and lepton masses m_t',m_b' < 400 GeV and
> 900 GeV, respectively. Whether or not the 750 GeV \gamma \gamma resonance is
confirmed, interesting phenomenology emerges in q' - Higgs systems (q'=t',b'),
that can be searched for at the LHC. For example, the heavy scalar states of
the model, S=H,A,H^+, may have BR(S -> q'q') ~ O(1), giving rise to observable
q'q' signals on resonance, followed by the flavor changing q' decays t'->uh
(u=u,c) and/or b'->dh (d=d,s,b). This leads to distinct high jet-multiplicity
signatures, with or without charged leptons, of the form q'q' -> (nj + mb +
lW)_S (j and b being light and b-quark jets, respectively), with n+m+l =6-8 and
unique kinematic features. It is also shown that the 4G2HDM can easily
accommodate the interesting recent indications of a percent-level branching
ratio in the lepton-flavor-violating (LFV) decay of the 125
GeV Higgs, if confirmed.Comment: 13 pages, late
SSD์ ๊ธด ๊ผฌ๋ฆฌ ์ง์ฐ์๊ฐ ๋ฌธ์ ์ํ๋ฅผ ์ํ ๊ฐํํ์ต์ ์ ์ฉ
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ)--์์ธ๋ํ๊ต ๋ํ์ :๊ณต๊ณผ๋ํ ์ปดํจํฐ๊ณตํ๋ถ,2020. 2. ์ ์น์ฃผ.NAND flash memory is widely used in a variety of systems, from realtime embedded systems to high-performance enterprise server systems. Flash memory has (1) erase-before-write (write-once) and (2) endurance problems. To handle the erase-before-write feature, apply a flash-translation layer (FTL). Currently, the page-level mapping method is mainly used to reduce the latency increase caused by the write-once and block erase characteristics of flash memory.
Garbage collection (GC) is one of the leading causes of long-tail latency, which increases more than 100 times the average latency at 99th percentile. Therefore, real-time systems or quality-critical systems cannot satisfy given requirements such as QoS restrictions.
As flash memory capacity increases, GC latency also tends to increase. This is because the block size (the number of pages included in one block) of the flash memory increases as the capacity of the flash memory increases. GC latency is determined by valid page copy and block erase time. Therefore, as block size increases, GC latency also increases.
Especially, the block size gets increased from 2D to 3D NAND flash memory, e.g., 256 pages/block in 2D planner NAND flash memory and 768 pages/block in 3D NAND flash memory. Even in 3D NAND flash memory, the block size is expected to continue to increase. Thus, the long write latency problem incurred by GC can become more serious in 3D NAND flash memory-based storage.
In this dissertation, we propose three versions of the novel GC scheduling method based on reinforcement learning. The purpose of this method is to reduce the long tail latency caused by GC by utilizing the idle time
of the storage system. Also, we perform a quantitative analysis for the RL-assisted GC solution.
RL-assisted GC scheduling technique was proposed which learns the storage access behavior online and determines the number of GC operations to exploit the idle time. We also presented aggressive methods,
which helps in further reducing the long tail latency by aggressively performing fine-grained GC operations.
We also proposed a technique that dynamically manages key states in RL-assisted GC to reduce the long-tail latency. This technique uses many fine-grained pieces of information as state candidates and manages key
states that suitably represent the characteristics of the workload using a relatively small amount of memory resource. Thus, the proposed method can reduce the long-tail latency even further.
In addition, we presented a Q-value prediction network that predicts the initial Q-value of a newly inserted state in the Q-table cache. The integrated solution of the Q-table cache and Q-value prediction network
can exploit the short-term history of the system with a low-cost Q-table cache. It is also equipped with a small network called Q-value prediction network to make use of the long-term history and provide good Q-value
initialization for the Q-table cache. The experiments show that our proposed method reduces by 25%-37% the long tail latency compared to the state-of-the-art method.๋ธ๋ ํ๋์ ๋ฉ๋ชจ๋ฆฌ๋ ์ค์๊ฐ ์๋ฒ ๋๋ ์์คํ
์ผ๋ก๋ถํฐ ๊ณ ์ฑ๋ฅ์ ์ํฐํ๋ผ์ด์ฆ ์๋ฒ ์์คํ
๊น์ง ๋ค์ํ ์์คํ
์์ ๋๋ฆฌ ์ฌ์ฉ ๋๊ณ ์๋ค. ํ๋์ ๋ฉ๋ชจ๋ฆฌ๋ (1) erase-before-write (write-once)์ (2) endurance ๋ฌธ์ ๋ฅผ ๊ฐ๊ณ ์๋ค. Erase-before-write ํน์ฑ์ ๋ค๋ฃจ๊ธฐ ์ํด flash-translation layer (FTL)์ ์ ์ฉ ํ๋ค. ํ์ฌ ํ๋์ ๋ฉ๋ชจ๋ฆฌ์ write-once ํน์ฑ๊ณผ block eraseํน์ฑ์ผ๋ก ์ธํ latency ์ฆ๊ฐ๋ฅผ ๊ฐ์ ์ํค๊ธฐ ์ํ์ฌ page-level mapping๋ฐฉ์์ด ์ฃผ๋ก ์ฌ์ฉ ๋๋ค.
Garbage collection (GC)์ 99th percentile์์ ํ๊ท ์ง์ฐ์๊ฐ์ 100๋ฐฐ ์ด์ ์ฆ๊ฐํ๋ long tail latency๋ฅผ ์ ๋ฐ์ํค๋ ์ฃผ์ ์์ธ ์ค ํ๋์ด๋ค. ๋ฐ๋ผ์ ์ค์๊ฐ ์์คํ
์ด๋ quality-critical system์์๋ Quality of Service (QoS) ์ ํ๊ณผ ๊ฐ์ ์ฃผ์ด์ง ์๊ตฌ ์กฐ๊ฑด์ ๋ง์กฑ ์ํฌ ์ ์๋ค.
ํ๋์ ๋ฉ๋ชจ๋ฆฌ์ ์ฉ๋์ด ์ฆ๊ฐํจ์ ๋ฐ๋ผ GC latency๋ ์ฆ๊ฐํ๋ ๊ฒฝํฅ์ ๋ณด์ธ๋ค. ์ด๊ฒ์ ํ๋์ ๋ฉ๋ชจ๋ฆฌ์ ์ฉ๋์ด ์ฆ๊ฐ ํจ์ ๋ฐ๋ผ ํ๋์ ๋ฉ๋ชจ๋ฆฌ์ ๋ธ๋ก ํฌ๊ธฐ (ํ๋์ ๋ธ๋ก์ด ํฌํจํ๊ณ ์๋ ํ์ด์ง์ ์)๊ฐ ์ฆ๊ฐ ํ๊ธฐ ๋๋ฌธ์ด๋ค. GC latency๋ valid page copy์ block erase ์๊ฐ์ ์ํด ๊ฒฐ์ ๋๋ค. ๋ฐ๋ผ์, ๋ธ๋ก ํฌ๊ธฐ๊ฐ ์ฆ๊ฐํ๋ฉด, GC latency๋ ์ฆ๊ฐ ํ๋ค.
ํนํ, ์ต๊ทผ 2D planner ํ๋์ ๋ฉ๋ชจ๋ฆฌ์์ 3D vertical ํ๋์ ๋ฉ๋ชจ๋ฆฌ ๊ตฌ์กฐ๋ก ์ ํ๋จ์ ๋ฐ๋ผ ๋ธ๋ก ํฌ๊ธฐ๋ ์ฆ๊ฐ ํ์๋ค.
์ฌ์ง์ด 3D vertical ํ๋์ ๋ฉ๋ชจ๋ฆฌ์์๋ ๋ธ๋ก ํฌ๊ธฐ๊ฐ ์ง์์ ์ผ๋ก ์ฆ๊ฐ ํ๊ณ ์๋ค. ๋ฐ๋ผ์ 3D vertical ํ๋์ ๋ฉ๋ชจ๋ฆฌ์์ long tail latency ๋ฌธ์ ๋ ๋์ฑ ์ฌ๊ฐํด ์ง๋ค.
๋ณธ ๋
ผ๋ฌธ์์ ์ฐ๋ฆฌ๋ ๊ฐํํ์ต(Reinforcement learning, RL)์ ์ด์ฉํ ์ธ ๊ฐ์ง ๋ฒ์ ์ ์๋ก์ด GC scheduling ๊ธฐ๋ฒ์ ์ ์ํ์๋ค. ์ ์๋ ๊ธฐ์ ์ ๋ชฉ์ ์ ์คํ ๋ฆฌ์ง ์์คํ
์ idle ์๊ฐ์ ํ์ฉํ์ฌ GC์ ์ํด ๋ฐ์๋ long tail latency๋ฅผ ๊ฐ์ ์ํค๋ ๊ฒ์ด๋ค. ๋ํ, ์ฐ๋ฆฌ๋ RL-assisted GC ์๋ฃจ์
์ ์ํ ์ ๋ ๋ถ์ ํ์๋ค.
์ฐ๋ฆฌ๋ ์คํ ๋ฆฌ์ง์ access behavior๋ฅผ ์จ๋ผ์ธ์ผ๋ก ํ์ตํ๊ณ , idle ์๊ฐ์ ํ์ฉํ ์ ์๋ GC operation์ ์๋ฅผ ๊ฒฐ์ ํ๋ RL-assisted GC scheduling ๊ธฐ์ ์ ์ ์ ํ์๋ค. ์ถ๊ฐ์ ์ผ๋ก ์ฐ๋ฆฌ๋ ๊ณต๊ฒฉ์ ์ธ ๋ฐฉ๋ฒ์ ์ ์ ํ์๋ค. ์ด ๋ฐฉ๋ฒ์ ์์ ๋จ์์ GC operation๋ค์ ๊ณต๊ฒฉ์ ์ผ๋ก ์ํ ํจ์ผ๋ก์จ, long tail latency๋ฅผ ๋์ฑ ๊ฐ์ ์ํฌ ์ ์๋๋ก ๋์์ ์ค๋ค.
๋ํ ์ฐ๋ฆฌ๋ long tail latency๋ฅผ ๋์ฑ ๊ฐ์์ํค๊ธฐ ์ํ์ฌ RL-assisted GC์ key state๋ค์ ๋์ ์ผ๋ก ๊ด๋ฆฌํ ์ ์๋ Q-table cache ๊ธฐ์ ์ ์ ์ ํ์๋ค. ์ด ๊ธฐ์ ์ state ํ๋ณด๋ก ๋งค์ฐ ๋ง์ ์์ ์ธ๋ฐํ ์ ๋ณด๋ค์ ์ฌ์ฉ ํ๊ณ , ์๋์ ์ผ๋ก ์์ ๋ฉ๋ชจ๋ฆฌ ๊ณต๊ฐ์ ์ด์ฉํ์ฌ workload์ ํน์ฑ์ ์ ์ ํ๊ฒ ํํ ํ ์ ์๋ key state๋ค์ ๊ด๋ฆฌ ํ๋ค. ๋ฐ๋ผ์, ์ ์๋ ๋ฐฉ๋ฒ์ long tail latency๋ฅผ ๋์ฑ ๊ฐ์ ์ํฌ ์ ์๋ค.
์ถ๊ฐ์ ์ผ๋ก, ์ฐ๋ฆฌ๋ Q-table cache์ ์๋กญ๊ฒ ์ถ๊ฐ๋๋ state์ ์ด๊ธฐ๊ฐ์ ์์ธกํ๋ Q-value prediction network (QP Net)๋ฅผ ์ ์ ํ์๋ค. Q-table cache์ QP Net์ ํตํฉ ์๋ฃจ์
์ ์ ๋น์ฉ์ Q-table cache๋ฅผ ์ด์ฉํ์ฌ ๋จ๊ธฐ๊ฐ์ ๊ณผ๊ฑฐ ์ ๋ณด๋ฅผ ํ์ฉ ํ ์ ์๋ค. ๋ํ ์ด๊ฒ์ QP Net์ด๋ผ๊ณ ๋ถ๋ฅด๋ ์์ ์ ๊ฒฝ๋ง์ ์ด์ฉํ์ฌ ํ์ตํ ์ฅ๊ธฐ๊ฐ์ ๊ณผ๊ฑฐ ์ ๋ณด๋ฅผ ์ฌ์ฉํ์ฌ Q-table cache์ ์๋กญ๊ฒ ์ฝ์
๋๋ state์ ๋ํด ์ข์ Q-value ์ด๊ธฐ๊ฐ์ ์ ๊ณตํ๋ค. ์คํ๊ฒฐ๊ณผ๋ ์ ์ํ ๋ฐฉ๋ฒ์ด state-of-the-art ๋ฐฉ๋ฒ์ ๋น๊ตํ์ฌ 25%-37%์ long tail latency๋ฅผ ๊ฐ์ ์์ผฐ์์ ๋ณด์ฌ์ค๋ค.Chapter 1 Introduction 1
Chapter 2 Background 6
2.1 System Level Tail Latency 6
2.2 Solid State Drive 10
2.2.1 Flash Storage Architecture and Garbage Collection 10
2.3 Reinforcement Learning 13
Chapter 3 Related Work 17
Chapter 4 Small Q-table based Solution to Reduce Long Tail Latency 23
4.1 Problem and Motivation 23
4.1.1 Long Tail Problem in Flash Storage Access Latency 23
4.1.2 Idle Time in Flash Storage 24
4.2 Design and Implementation 26
4.2.1 Solution Overview 26
4.2.2 RL-assisted Garbage Collection Scheduling 27
4.2.3 Aggressive RL-assisted Garbage Collection Scheduling 33
4.3 Evaluation 35
4.3.1 Evaluation Setup 35
4.3.2 Results and Discussion 39
Chapter 5 Q-table Cache to Exploit a Large Number of States at Small Cost 52
5.1 Motivation 52
5.2 Design and Implementation 56
5.2.1 Solution Overview 56
5.2.2 Dynamic Key States Management 61
5.3 Evaluation 67
5.3.1 Evaluation Setup 67
5.3.2 Results and Discussion 67
Chapter 6 Combining Q-table cache and Neural Network to Exploit both Long and Short-term History 73
6.1 Motivation and Problem 73
6.1.1 More State Information can Further Reduce Long Tail Latency 73
6.1.2 Locality Behavior of Workload 74
6.1.3 Zero Initialization Problem 75
6.2 Design and Implementation 77
6.2.1 Solution Overview 77
6.2.2 Q-table Cache for Action Selection 80
6.2.3 Q-value Prediction 83
6.3 Evaluation 87
6.3.1 Evaluation Setup 87
6.3.2 Storage-Intensive Workloads 89
6.3.3 Latency Comparison: Overall 92
6.3.4 Q-value Prediction Network Effects on Latency 97
6.3.5 Q-table Cache Analysis 110
6.3.6 Immature State Analysis 113
6.3.7 Miscellaneous Analysis 116
6.3.8 Multi Channel Analysis 121
Chapter 7 Conculsion and Future Work 138
7.1 Conclusion 138
7.2 Future Work 140
Bibliography 143
๊ตญ๋ฌธ์ด๋ก 154Docto
Finite-size scaling and boundary effects in two-dimensional valence-bond-solids
Various lattice geometries and boundaries are used to investigate
valence-bond-solid (VBS) ordering in the ground state of an S=1/2
square-lattice quantum spin model---the J-Q model, in which 4- or 6-spin
interactions Q are added to the Heisenberg exchange J. Ground state results for
finite systems (with up to thousands of spins) are obtained using a projector
QMC method. Great care has to be taken when extrapolating the order parameter
to infinite size, in particular in cylinder geometry. Even though strong 2D VBS
order exists and is established clearly with increasing system size on L*L
lattices (or Lx* Ly lattices with a fixed Lx/Ly), only short-range VBS
correlations are observed on long cylinders (when Lx -> infinity at fixed Ly).
The correlation length increases with Ly, until long-range order sets in at a
"critical" Ly. This width is large even when the 2D order is strong, e.g, for a
system where the order parameter is 70% of the largest possible value, Ly=8 is
required for ordering. Correlation functions for small L*L lattices can also be
misleading. For a 20%-ordered system results for L up to 20 appear to
extrapolate to a vanishing order parameter, while for larger L the behavior
crosses over and extrapolates to a non-zero value (with exponentially small
finite size corrections). The VBS order also exhibits interesting edge effects
related to emergent U(1) symmetry, which, if not considered properly, can lead
to wrong conclusions for the thermodynamic limit. The finite-size behavior for
small L*L lattices and long cylinders is similar to that predicted for a Z2
spin liquid. The results raise concerns about recent works claiming Z2 spin
liquid ground states in frustrated 2D systems, in particular, the Heisenberg
model with nearest and next-nearest-neighbor couplings. VBS state in this
system cannot be ruled out.Comment: 26 pages, 28 figures. v2: final, published versio
- โฆ