83 research outputs found
LL/SC and Atomic Copy: Constant Time, Space Efficient Implementations Using Only Pointer-Width CAS
When designing concurrent algorithms, Load-Link/Store-Conditional (LL/SC) is
often the ideal primitive to have because unlike Compare and Swap (CAS), LL/SC
is immune to the ABA problem. However, the full semantics of LL/SC are not
supported by any modern machine, so there has been a significant amount of work
on simulations of LL/SC using Compare and Swap (CAS), a synchronization
primitive that enjoys widespread hardware support. All of the algorithms so far
that are constant time either use unbounded sequence numbers (and thus base
objects of unbounded size), or require space for LL/SC object
(where is the number of processes). We present a constant time
implementation of LL/SC objects using space, where is
the maximum number of overlapping LL/SC operations per process (usually a
constant), and requiring only pointer-sized CAS objects. Our implementation can
also be used to implement -word objects in time (for
both and ) and space. To achieve these bounds, we
begin by implementing a new primitive called Single-Writer Copy which takes a
pointer to a word sized memory location and atomically copies its contents into
another object. The restriction is that only one process is allowed to
write/copy into the destination object at a time. We believe this primitive
will be very useful in designing other concurrent algorithms as well
Step Optimal Implementations of Large Single-Writer Registers
We present two wait-free algorithms for simulating an l-bit single-writer register from k-bit single-writer registers, for any k >= 1. Our first algorithm has big-theta(l/k) step complexity for both Read and Write and uses big-theta (4^(l-k)) registers. An interesting feature of the algorithm is that Read operations do not write to shared variables. Our second algorithm has big-theta (l/k + (log n)/k) step complexity for both Read and Write, where n is the number of readers, but uses only big-theta (nl/k + n(log n)/k) registers. Combining both algorithms gives an implementation with big-theta (l/k) step complexity using big-theta (nl/k) space for any 1 <= k < l.
We also prove that any implementation with big-O (l/k) step complexity for Read requires big-omega (l/k) step complexity for Write. Since reading l-bits requires at least ceiling(l/k) reads of k-bit registers, our lower bound shows that our implementation is step optimal
Short Proofs Are Hard to Find
We obtain a streamlined proof of an important result by Alekhnovich and Razborov [Michael Alekhnovich and Alexander A. Razborov, 2008], showing that it is hard to automatize both tree-like and general Resolution. Under a different assumption than [Michael Alekhnovich and Alexander A. Razborov, 2008], our simplified proof gives improved bounds: we show under ETH that these proof systems are not automatizable in time n^f(n), whenever f(n) = o(log^{1/7 - epsilon} log n) for any epsilon > 0. Previously non-automatizability was only known for f(n) = O(1). Our proof also extends fairly straightforwardly to prove similar hardness results for PCR and Res(r)
Brief Announcement: Survey of Persistent Memory Correctness Conditions
In this brief paper, we survey existing correctness definitions for concurrent persistent programs
The Effect of Race/Ethnicity on the Age of Colon Cancer Diagnosis
ABSTRACT
BACKGROUND: Colorectal cancer is the third most commonly diagnosed cancer in the United States. Notably, racial/ethnic disparities exist in both incidence and mortality.
PURPOSE: The aim of this case study was to investigate the impact of race/ethnicity on age at diagnosis of colorectal cancer in a defined population in Suffolk County, NY.
METHODS: Data were retrospectively collected on race/ethnicity, health insurance status, age at diagnosis, stage at diagnosis, gender, smoking status, alcohol intake, tumor location, and body mass index for colorectal cancer patients with medical records in the Stony Brook University Medical Center database (2005-2011). Population-based data on Hispanic and non-Hispanic Whites were obtained from the Surveillance, Epidemiology, and End Results registry of New York State for an overlapping time period. Permutation-based ANCOVA and logistic regression with stepwise variable selection were conducted to identify covariates and first-order interactions associated with younger age at diagnosis and cancer stage as a dependent categorical variable. RESULTS: Of 328 colorectal cancer patients, Hispanics were diagnosed at a median younger age of 57y vs. 67y than non-Hispanic Whites (FDR = 0.001). Twenty-six percent of Hispanics were diagnosed with colorectal cancer prior to the recommended age (50y) for colorectal cancer surveillance compared to 11% of non-Hispanic Whites (FDR =0.007). Analysis of New York State registry data corroborated our findings that Hispanic colorectal cancer patients were diagnosed at a median younger age than non-Hispanic Whites. Permutation-based ANCOVA identified race/ethnicity and health insurance as significantly associated with age of diagnosis (P=0.001). Logistic regression selected (younger) age at diagnosis as being significantly associated with stage IV disease. The limitations of the case study reside in the use of self-reporting of race and ethnicity and in the small sample sizes.
CONCLUSIONS: Hispanics may be at higher risk for colorectal cancer (y) and younger age at diagnosis is associated with advanced disease
Sensing as a Service in 6G Perceptive Networks: A Unified Framework for ISAC Resource Allocation
In the upcoming next-generation (5G-Advanced and 6G) wireless networks,
sensing as a service will play a more important role than ever before.
Recently, the concept of perceptive network is proposed as a paradigm shift
that provides sensing and communication (S&C) services simultaneously. This
type of technology is typically referred to as Integrated Sensing and
Communications (ISAC). In this paper, we propose the concept of sensing quality
of service (QoS) in terms of diverse applications. Specifically, the
probability of detection, the Cramer-Rao bound (CRB) for parameter estimation
and the posterior CRB for moving target indication are employed to measure the
sensing QoS for detection, localization, and tracking, respectively. Then, we
establish a unified framework for ISAC resource allocation, where the fairness
and the comprehensiveness optimization criteria are considered for the
aforementioned sensing services. The proposed schemes can flexibly allocate the
limited power and bandwidth resources according to both S&C QoSs. Finally, we
study the performance trade-off between S&C services in different resource
allocation schemes by numerical simulations
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