85 research outputs found
Complex Incremental Sheet Forming Using Back Die Support on Aluminium 2024, 5083 and 7075 alloys
Peer reviewedPublisher PD
StaticFixer: From Static Analysis to Static Repair
Static analysis tools are traditionally used to detect and flag programs that
violate properties. We show that static analysis tools can also be used to
perturb programs that satisfy a property to construct variants that violate the
property. Using this insight we can construct paired data sets of unsafe-safe
program pairs, and learn strategies to automatically repair property
violations. We present a system called \sysname, which automatically repairs
information flow vulnerabilities using this approach. Since information flow
properties are non-local (both to check and repair), \sysname also introduces a
novel domain specific language (DSL) and strategy learning algorithms for
synthesizing non-local repairs. We use \sysname to synthesize strategies for
repairing two types of information flow vulnerabilities, unvalidated dynamic
calls and cross-site scripting, and show that \sysname successfully repairs
several hundred vulnerabilities from open source {\sc JavaScript} repositories,
outperforming neural baselines built using {\sc CodeT5} and {\sc Codex}. Our
datasets can be downloaded from \url{http://aka.ms/StaticFixer}
Trypanosoma evansi u deva, magaraca i pasa u Indiji: usporedba rezultata pretrage lančanom reakcijom polimerazom i svjetlosnim mikroskopom
The objective of the present study was to compare two methods: PCR and blood smear examination for sensitive and specific detection of Trypanosoma evansi in camels, donkeys and dogs. Out of 131 blood samples tested, (61 camels, 44 donkeys and 26 dogs), 26 samples (21 camels, 3 donkeys and 2 dogs) were detected positive by PCR. Blood smear examination revealed the T. evansi organisms in only two camels.Svrha ovoga istraživanja bila je usporediti osjetljivost i specifičnost lančane reakcije polimerazom i pretrage krvnih razmazaka svjetlosnim mikroskopom za dokazivanje vrste Trypanosoma evansi u deva, magaraca i pasa. Od 131 pretraženoga krvnoga uzorka (61 od deva, 44 od magaraca i 26 od pasa), 26 uzoraka (21 od deva, tri od magaraca i dva od pasa) bilo je pozivno na osnovi pretrage lančanom reakcijom polimerazom. Pretragom krvnih
razmazaka svjetlosnim mikroskopom T. evansi dokazana je samo u dvije deve
Trypanosoma evansi u deva, magaraca i pasa u Indiji: usporedba rezultata pretrage lančanom reakcijom polimerazom i svjetlosnim mikroskopom
The objective of the present study was to compare two methods: PCR and blood smear examination for sensitive and specific detection of Trypanosoma evansi in camels, donkeys and dogs. Out of 131 blood samples tested, (61 camels, 44 donkeys and 26 dogs), 26 samples (21 camels, 3 donkeys and 2 dogs) were detected positive by PCR. Blood smear examination revealed the T. evansi organisms in only two camels.Svrha ovoga istraživanja bila je usporediti osjetljivost i specifičnost lančane reakcije polimerazom i pretrage krvnih razmazaka svjetlosnim mikroskopom za dokazivanje vrste Trypanosoma evansi u deva, magaraca i pasa. Od 131 pretraženoga krvnoga uzorka (61 od deva, 44 od magaraca i 26 od pasa), 26 uzoraka (21 od deva, tri od magaraca i dva od pasa) bilo je pozivno na osnovi pretrage lančanom reakcijom polimerazom. Pretragom krvnih
razmazaka svjetlosnim mikroskopom T. evansi dokazana je samo u dvije deve
TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings
In response to innovations in machine learning (ML) models, production
workloads changed radically and rapidly. TPU v4 is the fifth Google domain
specific architecture (DSA) and its third supercomputer for such ML models.
Optical circuit switches (OCSes) dynamically reconfigure its interconnect
topology to improve scale, availability, utilization, modularity, deployment,
security, power, and performance; users can pick a twisted 3D torus topology if
desired. Much cheaper, lower power, and faster than Infiniband, OCSes and
underlying optical components are <5% of system cost and <3% of system power.
Each TPU v4 includes SparseCores, dataflow processors that accelerate models
that rely on embeddings by 5x-7x yet use only 5% of die area and power.
Deployed since 2020, TPU v4 outperforms TPU v3 by 2.1x and improves
performance/Watt by 2.7x. The TPU v4 supercomputer is 4x larger at 4096 chips
and thus ~10x faster overall, which along with OCS flexibility helps large
language models. For similar sized systems, it is ~4.3x-4.5x faster than the
Graphcore IPU Bow and is 1.2x-1.7x faster and uses 1.3x-1.9x less power than
the Nvidia A100. TPU v4s inside the energy-optimized warehouse scale computers
of Google Cloud use ~3x less energy and produce ~20x less CO2e than
contemporary DSAs in a typical on-premise data center.Comment: 15 pages; 16 figures; to be published at ISCA 2023 (the International
Symposium on Computer Architecture
In-Datacenter Performance Analysis of a Tensor Processing Unit
Many architects believe that major improvements in cost-energy-performance
must now come from domain-specific hardware. This paper evaluates a custom
ASIC---called a Tensor Processing Unit (TPU)---deployed in datacenters since
2015 that accelerates the inference phase of neural networks (NN). The heart of
the TPU is a 65,536 8-bit MAC matrix multiply unit that offers a peak
throughput of 92 TeraOps/second (TOPS) and a large (28 MiB) software-managed
on-chip memory. The TPU's deterministic execution model is a better match to
the 99th-percentile response-time requirement of our NN applications than are
the time-varying optimizations of CPUs and GPUs (caches, out-of-order
execution, multithreading, multiprocessing, prefetching, ...) that help average
throughput more than guaranteed latency. The lack of such features helps
explain why, despite having myriad MACs and a big memory, the TPU is relatively
small and low power. We compare the TPU to a server-class Intel Haswell CPU and
an Nvidia K80 GPU, which are contemporaries deployed in the same datacenters.
Our workload, written in the high-level TensorFlow framework, uses production
NN applications (MLPs, CNNs, and LSTMs) that represent 95% of our datacenters'
NN inference demand. Despite low utilization for some applications, the TPU is
on average about 15X - 30X faster than its contemporary GPU or CPU, with
TOPS/Watt about 30X - 80X higher. Moreover, using the GPU's GDDR5 memory in the
TPU would triple achieved TOPS and raise TOPS/Watt to nearly 70X the GPU and
200X the CPU.Comment: 17 pages, 11 figures, 8 tables. To appear at the 44th International
Symposium on Computer Architecture (ISCA), Toronto, Canada, June 24-28, 201
Health sector spending and spending on HIV/AIDS, tuberculosis, and malaria, and development assistance for health: progress towards Sustainable Development Goal 3
Sustainable Development Goal (SDG) 3 aims to “ensure healthy lives and promote well-being for all at all ages”. While a substantial effort has been made to quantify progress towards SDG3, less research has focused on tracking spending towards this goal. We used spending estimates to measure progress in financing the priority areas of SDG3, examine the association between outcomes and financing, and identify where resource gains are most needed to achieve the SDG3 indicators for which data are available
Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-Adjusted life-years for 29 cancer groups, 1990 to 2017 : A systematic analysis for the global burden of disease study
Importance: Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. Objective: To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. Evidence Review: We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-Adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. Findings: In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572000 deaths and 15.2 million DALYs), and stomach cancer (542000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601000 deaths and 17.4 million DALYs), TBL cancer (596000 deaths and 12.6 million DALYs), and colorectal cancer (414000 deaths and 8.3 million DALYs). Conclusions and Relevance: The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care. © 2019 American Medical Association. All rights reserved.Peer reviewe
- …