The Architectural Implications of
Pipeline and Batch Sharing in Scienti?c Workloads
Douglas Thain,John Bent,Andrea C.Arpaci-Dusseau,Remzi H.Arpaci-Dusseau,and Miron Livny
Technical Report1463
22January2002
Computer Sciences Department
University of Wisconsin,Madison
Abstract
We present a study of six batch-pipelined scienti?c work-loads.Whereas other studies focus on the behavior of a sin-gle application,we characterize an emerging type of work-load which consists of pipelines of sequential processes that use?le storage for communication and also share signi?-cant data across a batch.This study includes measurements of the memory,CPU,and I/O requirements of individual components as well as analyses of I/O sharing within com-plete batches,as well as a discussion of the architectural rami?cations of these new types of workloads.
1.Introduction
For many years,researchers have understood the impor-tance of studying workload characteristics in order to eval-uate their impact on current and future systems architec-ture[6,18,20,27,31].Most of these previous applica-tion studies have focused on the detailed behavior of sin-gle applications,whether sequential or parallel.For exam-ple,the caching behavior of the SPEC workloads has long been a topic of intense scrutiny[7,12],and the communi-cation characteristics of parallel applications has similarly been well documented[9,37,36].
However,applications are no longer used in isolation in production settings.Whether in disparate settings such as graphics rendering[17],video production[33],or compu-tational science[13,14],the desired end-result is often the product of a group of applications,each of which may be run hundreds or thousands of times with varied inputs.
We refer to such workloads as batch-pipelined,as il-lustrated within Figure1.A batch-pipelined workload is composed of several independent pipelines;each pipeline contains sequential processes that communicate with
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Figure1.A Batch-Pipelined Workload
preceding and succeeding processes via private data?les. Shared input?les are used by all of the pipelines in various stages.As the?gure suggests,a workload is generally sub-mitted in large batches with all of the pipelines incidentally synchronized at the beginning.However,each pipeline is logically distinct and may correctly execute faster or slower than its siblings.
The key difference between studying the behavior of a single application and that of a batch-pipelined workload is that the sharing behavior of the batch-pipelined workload must be understood.For example,when many instances of the same application are run,the same executable and po-tentially many of the same input?les are used.Thus,to real-istically capture the full diversity of these production work-loads,one must study the behavior of the entire pipeline and account for the effects of sharing.
In this paper,we present a study of six production sci-enti?c workloads.We collected these application pipelines from diverse?elds of computational science,including as-tronomy,biology,geology,and physics;we believe the ap-plications are representative of a broad class of important workloads.We?rst present a basic characterization of the computational,memory,and I/O demands of these work-
loads.We?nd that although individually,a single pipeline does not place a tremendous load on system resources,in combination the loads can be overwhelming.We focus par-ticularly upon the I/O behavior of the workloads,because it is the primary source of sharing.We then characterize the sharing that occurs in the workloads,by breaking I/O activity into three categories:endpoint,which represents the input and?nal output,pipeline-shared,which is shared in a write-then-read fashion within a single pipeline,and batch-shared,which is comprised of input I/O is shared across pipelines.Through this characterization,we show that shared I/O is the dominant component of all I/O traf?c.
Most importantly,we study the implications for systems architecture,both from a hardware and software perspec-tive.We?nd that the architecture is strongly in?uenced by the different types of I/O traf?c,and analogous to proces-sors that differentiate instruction and data streams,systems must segregate I/O traf?c in order to be able to successfully scale under these workloads.Further,as workloads such as these are likely to be run in wide-area peer-to-peer comput-ing systems[11],we also study their behavior in such envi-ronments;extrapolating from current technology levels,we ?nd that while cluster interconnect bandwidth will likely keep up with processor technology advancements,wide-area bandwidth will likely become the bottleneck,poten-tially limiting such collaborative computing efforts.
The rest of this paper is organized as follows.In Sec-tion2,we describe the general characteristics of batch-pipelined workloads as well as our speci?c application pipelines.In Section3,we describe our experimental method,and in Section4,5,and6,we analyze the data and discuss architectural implications.We discuss related work in Section7,and conclude in Section8.
2.Applications
The applications that we characterize were chosen from a range of scienti?c disciplines.Our selection criteria were that the applications are attacking a major scienti?c ob-jective,are composed of sequential applications,and re-quire a scalable computing environment to accomplish high throughput.We focus mostly on six applications but in some measurements we include SETI@home[34]as a point of reference.With guidance from users,we chose workloads and input parameters to correspond to produc-tion use.For example,for CMS and AMANDA,we took the actual inputs used in current production runs.(More de-tails on the exact inputs will be included in the?nal version) A summary of the applications is found in Figure2.
Across these applications,we have observed the follow-ing characteristics behaviors:
An inverted hourglass storage pro?le.Small initial in-puts are generally created by humans or initialization tools and expanded by early stages into large intermediate re-sults.These intermediates are often reduced by later stages to small results to be interpreted by humans or incorporated into a database.Intermediate data,which often serves as checkpoint or cached values,may be ephemeral in nature. Multi-level working https://www.doczj.com/doc/815029737.html,ers can easily identify large logical collections of data needed by an application,such as calibration tables and physical constants.However,in a given execution,applications tend to select a small working set of which users are not aware;this has signi?cant conse-quences for data replication and caching techniques.
Signi?cant data sharing.Although each application has a large con?guration space,users submit large numbers of very similar jobs that access similar working sets.This property can be exploited for ef?cient wide-area distribu-tion over modest communication links.
3.Method
For each application,we capture its CPU,memory and I/O behavior.The CPU and memory behavior is tracked with available hardware counters and statistics.To instru-ment I/O behavior,we insert a shared library that replaces the I/O routines in the standard library.For each explicit I/O event requested by the application,the library records an event marking the start and end of the operation,the in-struction count,and other details about the I/O request.This technique can be applied to any application that is dynam-ically linked.Care is taken so as to avoid additional over-heads due to tracing.
Access to memory-mapped?les is traced with a user-level paging technique using the POSIX mprotect feature in a manner similar to that of Tempest[28].Access to memory-mapped regions generates a user-level page fault (SIGSEGV)that may be handled and traced by the shared library.Only one application(BLAST)uses memory-mapped I/O.In the analysis that follows,page faults are considered equivalent to explicit read operations of one page size and non-sequential access to memory-mapped pages is recorded as an explicit seek operation.
4.Workload Analysis
An overview of the resources consumed by each appli-cation is given in Figure3.These applications have a wide variance in run times on current hardware,ranging from a little more than a minute(BLAST)to a little more than a day (IBIS).Considered individually,these applications spend the majority of time consuming CPU rather than I/O,not requiring nearly the I/O capability as suggested by the Am-dahl/Case rule of thumb(1Mbit per second of I/O band-width per MIPS of CPU)[4].Memory requirements and
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Figure 2.Application Schematics These schematics summarize the structure of each application pipeline.Circles in-dicate individual processes,labeled with the name and user CPU time.Rounded boxes indicate data private to a pipeline.Double boxes indicate data shared between pipelines in a batch.Arrows indicate data ?https://www.doczj.com/doc/815029737.html,beled arrows indicate that actual I/O performed differs from the static ?le size.
·BLAST [3]searches genomic databases for matching proteins and nucleotides.Both queries and archived data may in-clude errors or gaps,and acceptable match similarity is parameterized.Exhaustive search is often necessary.A single executable,blastp ,reads a query sequence,searches through a shared database,and outputs matched sequences.
·IBIS [15]is a global-scale simulation of Earth systems.IBIS simulates effects of human activity on the global environment,i.e.,global warming.ibis performs the simulation and emits a series of snapshots of the global state.
·CMS [13]is a high-energy physics experiment to begin operation in 2006.CMS testing software is a two-stage pipeline;the ?rst stage,cmkin ,given a random seed,generates and models the behavior of particles accelerated by the ring.The output is a set of events that are fed to cmsim ,which simulates the response of the detector.The ?nal output represents events that exceed the triggering threshold of the detector.
·Nautilus [35]is a simulation of molecular dynamics.An input con?guration describes molecules within a three-dimensional space.Newton’s equation is solved for each particle.Incremental snapshots are taken to periodically capture particle coor-dinates.The ?nal snapshot is often passed back to the program as an initial con?guration for another simulation.Eventually,all snapshots are converted into a standard format using bin2coord and consolidated into images using rasmol .
·Messkit Hartree-Fock (HF)[8]is a simulation of the non-relativistic interactions between atomic nuclei and electrons,allowing the computation of properties such as bond strengths and reaction energies.Three distinct executables comprise the calculation:setup initializes data ?les from input parameters,argos computes and writes integrals corresponding to the atomic con?guration,and scf iteratively solves the self-consistent ?eld equations.
·AMANDA [14]is an astrophysics experiment designed to observe cosmic events such as gamma-ray bursts by collecting the resulting neutrinos through their interaction with the Earth’s mass.The ?rst stage of the calibration software,corsika ,simulates the production of neutrinos and the primary interaction which creates showers of muons.corama translates the
Real Millions of Instructions Memory(MB)I/O Traf?c I/O Rates Application Time(s)Integer Float Burst Text Data Share MB Ops MB/MIPS MB/s setiathome seti1953084.81523932.2 4.675.8417260 blast blastp12223.50.20.1330.188671
ibis ibis7215213.84389746.8104.7336.1110802
cms cmkin5260.4743.8 6.17.5988
15595.08.770.4 4.30.005290.24 total498256.1226423.40.43806.21916546 hf setup76.60.40.09.12953
597.60.9 2.5 1.40.00321 1.11 scf132670.15327.60.23983.4765562
617.60.910.3 1.40.013517.54
14047.60.3146.6 1.20.000220.02 bin2coord263954.4280837.2 4.2403.3129727
158.60.4 4.9 1.70.001760.81 total1100666.5735412.27.9802.7233681 amanda corsika160066.54203.626.424.06225
41.90.5 3.2 1.10.01300 1.18
mmc330189.17706.50.3154.41141633
3601.722.0256.6 1.60.005230.15 total578797.832330.70.5778.01161275
1475.77 3.02 3.0211 4.15 2.36 2.68
11330.11323.59586.2110.120.120.12
136336.0873.6473.64118196.0066.6666.66
47.49 3.88 3.8827.49 3.88 3.88
cmsim113735.2452.8663.05
173806.22119.88130.06670.9867.0167.01
59.130.400.403 3.690.390.40
argos20.040.030.26
113983.40664.61664.618 4.07 2.50 2.69 total93984.81663.80664.60
nautilus nautilus7 4.25 4.25 4.25
247403.27273.87273.87241250.49249.39249.39 rasmol124115.87115.88115.88
501802.66435.48435.48369529.76290.94290.94
823.9623.9623.96323.2123.2123.21 corama323.1723.1723.17
11154.36154.36154.362125.43125.43125.43 amasim227545.04545.09630.47
46778.04778.09863.427180.14180.11180.11
Figure4.I/O Volume
Appl.Open(%)Dup(%)Close(%)Read(%)Write(%)Seek(%)Stat(%)Other(%) seti0(0.0)64266(15.4)63154(15.1)15(0.0) 18(0.0)18(0.0)1556(1.8)37(0.0) ibis0(0.0)26866(24.2)51527(46.5)122(0.1) 2(0.2)2(0.2)492(49.8)8(0.8)
17(0.0)16(0.0)18468(1.0)47(0.0)
19(0.0)18(0.0)18960(1.0)55(0.0) setup0(0.0)1061(35.9)1118(37.9)6(0.2) argos0(0.0)8(0.0)127106(49.9)4(0.0) scf0(0.0)509642(66.6)254781(33.3)18(0.0) total0(0.0)510711(49.9)383005(37.4)28(0.0) 497(0.8)488(0.7)62573(95.5)678(1.0)
1190(0.9)12238(9.4)65109(50.2)407(0.3)
359(0.9)517(1.3)3457(9.0)252(0.7)
2046(0.9)13243(5.7)131139(56.1)1337(0.6) corsika0(0.0)199(3.2)8(0.1)10(0.2) corama0(0.0)5936(46.8)2(0.0)4(0.0) mmc0(0.0)29906(2.6)0(0.0)7(0.0) amasim20(0.0)577(78.7)4(0.5)10(1.4) total0(0.0)36618(3.2)14(0.0)31(0.0)
Figure5.I/O Instruction Mix
Endpoint I/O(MB)Pipeline I/O(MB)Batch I/O(MB) Application Files Traf?c Unique Static Files Traf?c Unique Static Files Traf?c Unique Static setiathome seti1275.43 2.68 2.68
blast blastp00.000.000.00
ibis ibis99148.2712.6912.69
cms cmkin17.42 3.81 3.81
663.5063.1363.1393729.6749.0459.24 total212.997.627.62
hf setup28.990.260.26
3 1.81 1.81 1.8100.000.000.00
scf73983.39664.59664.59
3 1.96 1.9
4 1.9410.000.000.00
6 1.18 1.10 1.102 3.14 3.14 3.14
bin2coord241403.25273.85273.85
11912.8812.8812.8830.080.090.09 total369785.37418.25418.25
amanda corsika323.1723.1723.17
30.000.000.0000.000.000.00
mmc6151.63151.63151.63
5 5.31 5.31 5.3122505.04505.04505.04
total11264.31264.29349.69
program sizes are all quite modest in comparison to total I/O volume.
Figure4details the I/O volume produced by each ap-
plication.We make several observations.Although these applications are conceived as a pipeline of multiple stages, they are not connected by simple data streams.Rather,each makes complex read/write use of the?le system,as indi-cated by the number of?les each accesses.SETI,CMS, HF,and to a lesser degree,BLAST,all read input data mul-tiples times.Over-writing of output data is also found in all pipelines with the exception of AMANDA.Output over-writing is usually done to update application-level check-points in place.We are somewhat alarmed to observe that such checkpoints are unsafely written directly over exist-ing data,rather than written to a new?le and atomically replaced with rename.Several pipelines are distributed with large collections of data that may be of use to many runs.However,any typical run only accesses a small por-tion common to similar runs.For example,the static size of the BLAST dataset exceeds the unique amount read by the application by45%.
The distribution of“I/O instructions”is given in Figure 5.Two features stand out.First,a high degree of ran-dom access is present throughout,with the exception of AMANDA.This results from the nature of the data?les accessed by the programs,generally with complex,self-referencing,internal structure,and contradicts many?le system studies which indicate the dominance of sequential I/O[5].Second,a very large number of opens are is-sued relative to the number of?les actually accessed.Typ-ically designed on standalone workstations,these applica-tions are not optimized for the realities of distributed com-puting,where opening a?le for access can be many times more expensive than issuing a read or write.The Other column sums a number of generally uncommon operations such as ioctl and access.The high numbers in this column re?ect the fact that bin2coord and rasmol are driven by shell scripts which perform many readdir op-erations.
5.Sharing Analysis
To characterize the different types of sharing in batch-pipelined workloads,we have divided the I/O traf?c into three roles.Endpoint traf?c consists of the initial inputs and ?nal outputs that are unique to each pipeline.They must be read from and written to the central site regardless of the system design.Pipeline traf?c consists of intermediate data passed between pipeline stages.Batch traf?c consists of input data that are identical across all pipelines.
Through our understanding of each application,we iden-ti?ed every?le accessed as either endpoint,pipeline,or batch,and computed the traf?c performed in each category,
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Figure7.Batch Working Set.These?gures show the hitrate of the batch I/O traf?c as a function of cache size with a batch width of10.Notice that most of these working sets are very small and even the largest as seen in AMANDA is only slightly more than half of a gigabyte.Further notice that maximum hit rates are achieved with cache sizes that are relatively small compared to the total batch I/O traf?c.
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Figure8.Pipeline Working Set.These?gures show the hitrate of the private I/O traf?c as a function of cache size. AMANDA is anomolous here because it has no pipelined I/O and thus needs no pipeline cache at all.For most of the other applications,notice that a small cache size rela-tive to the total private I/O of the application can achieve maximal hit rates.The exception is Nautilus which has an early plateau but is not maximized until its cache is almost the size of the total traf?c.
as shown in Figure6.We immediately see that compar-atively little traf?c is needed at the endpoints;the bulk is either pipeline or batch,depending on the application.To examine the sharing potential of each workload,we sepa-rated the pipeline and batch I/O traces and replayed them over cache simulators of various sizes.These results are shown in Figures7and8.What is evident from these re-sults is that the working sets(both batch and pipeline)of each of these applications is very low relative to their total I/O demands.This is an encouraging result as it shows that maximum hit rates can be achieved with small caches and in most cases this maximal hit rate will exceed90%.Note that the size of the executable?les is included implicitly in these calculations.
I /O R a t e
Batch Width
Batch Width
Batch Width
I /O R a t e
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All Data Endpoint and Pipeline Endpoint and Batch Endpoint Only
Figure 9.Scalability of I/O Roles
6.Architectural Implications
Each of these workloads are potentially in?nite.In these problem domains,the ability to harness more com-puting power enables higher resolution,more parameters,and lower statistical uncertainties.Current users of these applications wish to scale up throughput by running hun-dreds or thousands simultaneously.At this scale,applica-tions normally considered CPU-bound become I/O bound when considered in aggregate.
To give some idea of the growing envelope of current scienti?c computing,consider that in the spring of 2002,the CMS pipeline was used to simulate 5million events di-vided into 20,000pipelined jobs,consuming 6CPU-years and producing a terabyte of output.This batch was only a small fraction attempted as a test run before full production begins in 2007.Successive yearly workloads are planned to grow.All the necessary code and data are published in au-thoritative form by the experiment’s central site.Likewise,all simulation outputs must eventually be moved back for archival storage.
In this section,we will explore the general properties of computing and storage systems that may be built to satisfy these workloads.We will not explore detailed algorithms for data management,but instead consider the balance be-tween the necessary resources.
6.1.Endpoint Scalability
We assume that each of these applications,like CMS,relies on a central site for the authenticity and archival of input and output data.Thus,ultimate scalability is limited by competition for this shared resource.However,we have demonstrated that actual endpoint I/O traf?c is a relatively small fraction of the total for all of these applications.If we are able to eliminate all non-endpoint traf?c from the end-point server through techniques such as caching and repli-cation then we may see signi?cant gains in scalability.
Of course,traf?c elimination must be carried out care-fully.Pipeline-shared traf?c may only be eliminated if it is
truly of no use to the end user.Such intermediate data might be necessary to return for debugging or even for archival if the ability to reproduce it is questionable.Batch-shared may only be eliminated within the constraints of maintain-ing the consistency and authenticity of potentially changing input data.Traf?c elimination cannot be done blindly with-out some consideration of how the data are actually used outside the computing system.
That said,we may consider the limits of a system for executing such workloads based on its ability to eliminate shared traf?c.Figure 9shows how each of the selected applications would scale in four systems each eliminating some category of traf?c.We assume the presence of a buffering structure suf?cient to completely overlap all CPU and I/O;?gures assume a 2000MIPS CPU and show MB per second of CPU time.Two horizontal lines show mile-stones in I/O bandwidth.The lower,at 15MB/s,represents a capable commodity hard disk.The upper,at 1500MB/s,represents a very aggressive storage server and network.The leftmost graph shows the scalability of a system that carries all traf?c to the endpoint server.In this discipline,a high end storage device is needed for systems of very modest size,and is even overwhelmed by two applications near n=100.Only IBIS and SETI would be able to scale to n=100,000.If batch-shared traf?c is eliminated,we will make signi?cant improvements in CMS and Nautilus,as shown in the second graph.On the other hand,if pipeline-shared traf?c is eliminated,we observe signi?cant gains for SETI,HF,and Nautilus,as shown in the third.If only end-point I/O is performed,then we reach the limit shown in the rightmost graph.All of the applications shown could scale over 1000workers with modest storage,and over 100,000with high-end storage.SETI alone could potentially scale to 1million CPUs,an indicator of its specialized design for wide-area deployment.
6.2Hardware Architecture
To reach these scalability limits,we must provide a hard-ware architecture that localizes the effects of each of the I/O
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Figure 10.A General I/O Architecture
Each storage device in this architecture corresponds to the three roles of I/O:pipeline-shared (P),batch-shared (B),and endpoint (E).Each CPU owns a private pipeline-shared device,is connected to the batch-shared storage by a batch interconnect (BI)and then to the endpoint storage by an endpoint interconnect (EI).We consider a wide range of technologies –from I/O backplanes to wide-area networks –as candidates for both interconnects.
roles.We propose that there is a natural division of hard-ware resources into the three roles of endpoint,pipeline-shared,batch-shared.If suf?ciently powerful software can accurately classify traf?c,then scalable systems can be pro-visioned with the right amount of hardware to create a bal-anced system for the target workload.This provisioning is not necessarily that obtained by networking commodity desktop workstations into uniform clusters.
A general architecture is shown in Figure 10.There are three types of storage corresponding to the three roles of I/O traf?c.An endpoint (E)server is primarily responsible for serving unique input data and archiving output data.When necessary,it must also provide authentic copies of batch-shared data,although this role must be minimized.As we have mentioned,this service is necessarily the bottleneck of the system;a high-end network storage device may be necessary.To minimize load on the archive,batch-shared data are stored on batch-sharing (B)services in the network.These provide access to the read-only data common to all pipeline executions.Finally,each CPU is equipped with a device for temporary storage of pipeline-shared (P)data.For the application sizes presented here,P may simply be main memory.Such memory is logically distinct from other CPUs and needs no facilities for coherence or other commu-nication without the direction of the CPU.We will consider a range of technologies as candidates for the batch-sharing interconnect (BI)and the endpoint interconnect (EI).
Figure 11shows application performance and scalability of six candidate con?gurations.All are composed of 1024CPUs,connected by an aggressive 1500MB/s endpoint in-
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imizes system throughput measured in jobs completed per second.This throughput is then normalized against that of the slowest system,yielding a speedup ratio.The?nal three columns of Figure11also show the percent utilization of each resource,indicating which is the bottleneck.
The?rst con?guration is approximately the state of com-modity computing clusters in2002.Given an appropriate cluster size this technology may be made well-balanced for four of seven applications.It is far over-provisioned for SETI,and underprovisioned for BLAST.Moving down the table,upgrading the BI to125MB/s offers BLAST a speedup of4.25times,even with only two CPUs per BI. Other applications see no bene?t.Of these applications, BLAST may be the only one well-suited to commodity SMPs with small numbers of processors.
The fourth con?guration,using32BIPS processors and a12.5MB/s batch interconnect,might be the state of com-modity computing clusters in2008.Here,with smaller but still reasonable cluster sizes,IBIS,HF,and Nautilus may still be made well-balanced.AMANDA is under-provisioned,but may be satis?ed by advancing to faster networks.A single instance of BLAST will still consume the majority of a1250MB/s network,so distributing this computation will require I/O development to match CPU growth.However,CMS is in deeper trouble.It is not con-strained by the local area network,but with1024proces-sors,its global throughput is limited by the bandwidth of even a1500MB/s storage device.
Clearly,no single con?guration will satisfy all applica-tions.Any general-purpose system will be drastically over-or under-provisioned for a given application.However, careful allocation of resources to different classes of jobs may still yield a balanced system.For example,10242 BIPS CPUs connected by a125MB/s network could easily be shared by two instances of BLAST and1022instances of Nautilus,utilizing the CPU and BI and100and99percent, respectively.If such systems are to be used as commod-ity engines for scienti?c work,then network resources must rise to become an allocable resource in combination with CPU time and disk space.
6.3Software Architecture
These workloads,whether executed on conventional or custom architectures,have unusual demands of system soft-ware.They require something like a distributed?le system, that provides access to shared input data and output space via a consistent naming scheme within constraints of secu-rity,persistence,and performance.Traditional?le systems do not serve these applications because their naming and consistency requirements are targeted to interactive cooper-ating users.These applications require a data management system that has specialized requirements for workload anal-ysis,failure recovery,and resource management.
Scalable solutions to both pipeline and batch sharing problems require that an application’s I/O be classi?ed into each of the three roles with some degree of accuracy.Cus-tom applications such as SETI have succeeded in wide scalability by virtue of manual I/O division:all endpoint I/O happens via explicit network communication.Yet,we can hardly expect that all valuable applications will be re-written for a distributed environment.Ideally,such I/O roles would be detected automatically by the system,but we might reasonably ask the user to provide hints of I/O roles to the system without modifying applications directly.
A number of?le systems take account of the conven-tional wisdom that quickly-deleted data is a signi?cant source of traf?c in general-purpose workload.However, this recognition has limited application due to the require-ments of reliability and consistency in interactive systems. For example,NFS permits a30-60second delay between application writes and data movement to the server.Were this delay made to be minutes or hours in order to accommo-date pipeline sharing,the reduction in unnecessary writes would be accompanied by a much increased danger of data loss during a crash and some very unusual consistency se-mantics.The session semantics of AFS are even worse: closing a?le is a blocking operation that forces the write-back of dirty data.Not only would all vertically shared data be written back at each of the(numerous)close operations, but the CPU would be held idle between pipelines,offering no possibility of CPU-I/O overlap.
General-purpose?le systems operate under the assump-tion that most data must eventually?ow back to the archival site.These workloads require the opposite assumption: most created data should remain where it is created un-til an explicit operation by the writer,the system,or per-haps the user forces it into archival storage.This improves overlap and eliminates unnecessary writes,but runs the dan-ger that I/O operations waiting to be written back may fail, due to permissions,disconnection,or any of the many other sources of error in a distributed?le system.This is accept-able in a scienti?c batch computing system,as long as such a failed I/O can be detected,matched with the process that issued it,and force a re-execution of the job.Such seman-tics would not be appropriate in an interactive workload, where a user expects that I/O completion is immediate.
Input sharing has been accomplished in traditional?le systems through the use of client-side caches.Such caches have improved both scalability and performance by shar-ing recently-read data between processes However,cache misses are still resolved at the central server.This will not scale when many thousands of compute nodes begin exe-cuting the same program at once and all request the same input?les to?ll cold caches.To achieve scalability in batch sharing,a compute node must attempt to leverage the poten-
tially warm caches of its peers.Such techniques will seek to maximize scalability,even at the price of reduced single-client performance.
7.Related Work
The CPU,memory,communication,and I/O characteris-tics of applications have been studied for many years by the research community.These can be roughly categorized by the type of workloads that they consider:general-purpose workloads containing many applications,sequential appli-cations examined in isolation,or parallel applications in iso-lation.We summarize the work in each of these categories, focusing on those that have examined?le system activity.
File system activity has been examined for a range of general-purpose workloads.Many of the studies that have greatly in?uenced?le system design over the last20years focused on academic and research workloads[31,24,5,29]. These studies have found that most?les have very short lifetimes,access patterns exhibit a high degree of locality, and read-write sharing is rare.However,missing from these broad studies of traf?c is any linkage to the applications that generate the traf?c.
More similar to our work are those studies that have fo-cused on the behavior of individual applications.The mem-ory and I/O behavior of sequential applications received great attention during the early development of virtual-memory and?le cache mechanisms and policies in tra-ditional operating systems[22].For example,Denning’s working set model[10],initially applied to memory-access patterns,has also been examined as a model for sequential I/O behavior[19].As with?le systems,studies of commer-cial workloads[6,18]have become more common in recent years.However,in this domain,the interaction or pipeline behavior of sequential applications has not been examined. While we believe it may also be interesting to study the de-tailed memory-system behavior of our applications,we do not believe the opportunities for sharing are fundamentally different than other studies.
Parallel applications are in many ways the most similar to pipelined batch applications.The CPU,memory,com-munication,and I/O behavior of parallel and vector applica-tions have been quanti?ed in a number of studies[9,37,36], but the most relevant studies consider the impact of explicit I/O[30,32,23,8,1].Our study embellishes these works by studying the sharing behavior of an important new class of workload.
Many of these studies demonstrate the drastic differ-ences in I/O behavior for parallel applications compared to general-purpose workloads.For example,parallel scienti?c workloads often have high,bursty I/O rates[21,25]and relatively constant behavior across different runs and input parameters[25];further,parallel workloads tend to be dom-inated by the storage and retrieval costs of large?les,par-ticularly check-point?les[21,16];?nally,quick deletion is uncommon[16].
As many have observed,improvements in processor and memory speed have far outstripped improvements in I/O performance.Models of I/O system behavior[2,26]have relied on general rules such as Amdahl’s law to guide sys-tem design.A more detailed measurement of the interaction between I/O-intensive processes will serve to guide future models of systems and workloads.
8.Conclusions
Applications are not run in isolation.In production set-tings,scripting and work?ow tools are used to glue together series of applications into pipelines;a particular pipeline may be run many thousands of times over varied inputs to achieve the goals of the users.We term such workloads batch-pipelined,as batches of pipelines are run at a given instant.
In this paper,we characterize an important class of batch-pipelined workloads,within the realm of computa-tional science.Beyond typical characterizations of process-ing,memory,and I/O demands,we bring forth the sharing characteristics of the workloads,and demonstrate their im-portance on scalability.
We also study the architectural impacts of this workload class,from both a hardware and software perspective.The key to scalability of these workloads is I/O classi?cation;by segregating I/O traf?c by type,and aggressively exploiting sharing characteristics,scalability can be improved by many orders of magnitude.
As shared computing infrastructures and application out-sourcing become commonplace,the ability of scalable sys-tems to handle the demands of batch-pipelined workloads will become increasingly important.Studying the interac-tion of many such batch-pipelined workloads on a single platform is thus an interesting topic for future research.
9Acknowledgements
We gratefully acknowledge all of the people who helped us to install,operate,and understand these applications and their behavior,including Paolo Desiati,Zach Miller,Dierk Polzin,Daniel Reed,and Alan de Smet.Douglas Thain is supported by a Lawrence Landweber NCR Fellowship in Distributed Systems and the Wisconsin Alumni Research Foundation.
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尊重的素材（为人处世） 思路 人与人之间只有互相尊重才能友好相处 要让别人尊重自己，首先自己得尊重自己 尊重能减少人与人之间的摩擦 尊重需要理解和宽容 尊重也应坚持原则 尊重能促进社会成员之间的沟通 尊重别人的劳动成果 尊重能巩固友谊 尊重会使合作更愉快 和谐的社会需要彼此间的尊重 名言 施与人，但不要使对方有受施的感觉。帮助人，但给予对方最高的尊重。这是助人的艺术，也是仁爱的情操。—刘墉 卑己而尊人是不好的，尊己而卑人也是不好的。———徐特立 知道他自己尊严的人，他就完全不能尊重别人的尊严。———席勒 真正伟大的人是不压制人也不受人压制的。———纪伯伦 草木是靠着上天的雨露滋长的，但是它们也敢仰望穹苍。———莎士比亚 尊重别人，才能让人尊敬。———笛卡尔 谁自尊，谁就会得到尊重。———巴尔扎克 人应尊敬他自己，并应自视能配得上最高尚的东西。———黑格尔 对人不尊敬，首先就是对自己的不尊敬。———惠特曼
每当人们不尊重我们时，我们总被深深激怒。然而在内心深处，没有一个人十分尊重自己。———马克·吐温 忍辱偷生的人，绝不会受人尊重。———高乃依 敬人者，人恒敬之。———《孟子》 人必自敬，然后人敬之；人必自侮，然后人侮之。———扬雄 不知自爱反是自害。———郑善夫 仁者必敬人。———《荀子》 君子贵人而贱己，先人而后己。———《礼记》 尊严是人类灵魂中不可糟蹋的东西。———古斯曼 对一个人的尊重要达到他所希望的程度，那是困难的。———沃夫格纳 经典素材 1元和200元 （尊重劳动成果） 香港大富豪李嘉诚在下车时不慎将一元钱掉入车下，随即屈身去拾，旁边一服务生看到了，上前帮他拾起了一元钱。李嘉诚收起一元钱后，给了服务生200元酬金。 这里面其实包含了钱以外的价值观念。李嘉诚虽然巨富，但生活俭朴，从不挥霍浪费。他深知亿万资产，都是一元一元挣来的。钱币在他眼中已抽象为一种劳动，而劳动已成为他最重要的生存方式，他的所有财富，都是靠每天20小时以上的劳动堆积起来的。200元酬金，实际上是对劳动的尊重和报答，是不能用金钱衡量的。 富兰克林借书解怨 （尊重别人赢得朋友）
那一刻我感受到了幸福 本文是关于初中作文的那一刻我感受到了幸福，感谢您的阅读！ 每个人民的心中都有一粒幸福的种子，当它拥有了雨水的滋润和阳光的沐浴，它就会绽放出最美丽的姿态。那一刻，我们都能够闻到幸福的芬芳，我们都能够感受到幸福的存在。 在寒假期间，我偶然在授索电视频道，发现(百家讲坛)栏目中大学教授正在解密幸福，顿然引起我的好奇心，我放下了手中的遥控器，静静地坐在电视前，注视着频道上的每一个字，甚至用笔急速记在了笔记本上。我还记得，那位大学教授讲到了一个故事：一位母亲被公司升职到外国工作，这位母亲虽然十分高兴，但却又十分无奈，因为她的儿子马上要面临中考了，她不能撇下儿子迎接中考的挑战，于是她决定拒绝这了份高薪的工作，当有人问她为什么放弃这么好的机会时，她却毫无遗憾地说，纵然我能给予儿子最贵的礼物，优异的生活环境，但我却无当给予他关键时刻的那份呵护与关爱，或许以后的一切会证明我的选择是正确的。听完这样一段故事，我心中有种说不出的感觉，刹那间，我仿拂感觉那身边正在包饺子的妈妈，屋里正在睡觉的爸爸，桌前正在看小说的妹妹给我带来了一种温馨，幸福感觉。正如教授所说的那种解密幸福。就要选择一个明确的目标，确定自已追求的是什么，或许那时我还不能完全诠释幸福。 当幸福悄悄向我走来时，我已慢慢明白，懂得珍惜了。 那一天的那一刻对我来说太重要了，原本以为出差在外的父母早已忘了我的生日，只有妹妹整日算着日子。我在耳边唠叨个不停，没想到当日我失落地回到家中时，以为心中并不在乎生日，可是眼前的一切，让我心中涌现的喜悦，脸上露出的微笑证明我是在乎的。
爸爸唱的英文生日快乐歌虽然不是很动听，但爸爸对我的那份爱我听得很清楚，妈妈为我做的长寿面，我细细的品尝，吃出了爱的味道。妹妹急忙让我许下三个愿望，嘴里不停的唠叨：我知道你的三个愿望是什么?我问：为什么呀!我们是一家人，心连心呀!她高兴的说。 那一刻我才真正解开幸福的密码，感受到了真正的幸福，以前我无法理解幸福，即使身边有够多的幸福也不懂得欣赏，不懂得珍惜，只想拥有更好更贵的，其实幸福比物质更珍贵。 那一刻的幸福就是爱的升华，许多时候能让我们感悟幸福不是名利，物质。而是在血管里涌动着的，漫过心底的爱。 也许每一个人生的那一刻，就是我们幸运的降临在一个温馨的家庭中，而不是降临在孤独的角落里。 家的感觉就是幸福的感觉，幸福一直都存在于我们的身边!
首届“教育教学技能大比武”总结 为期半个月的青年教师首届“教育教学技能大比武”活动已经圆满落下帷幕。参加本次比赛的教师都是38周岁以下的青年教师，比赛内容包括讲课、答辩、三笔字、演讲四个环节。这次活动在学校领导的大力支持下，在全体教师的努力配合下，在参赛教师积极参与、认真准备下，取得圆满成功。 回顾本次比赛活动，老师们无论是在个人综合素质、教材把握能力还是在课堂驾驭能力上都有精彩的展示，下面对本次活动做一个总结： 一、讲课赛环节 这十九位青年教师对此次比赛高度重视，认真备课、讲课，为我们呈现了一节节风格各异、亮点纷呈的课，主要呈现了一下几个特点： 1、备课充分、设计用心。 老师们在备课过程中，能深入钻研教材，做了大量充分的准备。老师们都精心设计导语，创设情境，千方百计地激发起学生强烈的求知欲，能够把知识和能力深入浅出又扎扎实实的传授给学生，每一节课都朴实无华，每一节课都独具匠心，比如：郑珊老师在讲授《图形的旋转》一课时，教学设计层次分明，抓住平移和旋转的特征明确其描述方法，在新授的过程中能够放手让学生自己思考-动手操作-小组交流-展示（说明描述），老师引导学生亲历学习过程，通过几个有效的追问，使自己体会掌握了学习内容。 2、教学扎实有效，注重基础训练。 老师们能够抓住教学目标，精心设计每一个环节，同时老师们十分注重基础训练，比如高年级语文老师在教学中注重字词的品读与指导，在阅读教学中，老师能通过阅读来领悟文本的内涵，例如王玉英讲述《梅花魂》一课，她更注重引导学生“品词、品句、品读”以此让学生以读明理，以读悟情，通过“品”字让学生真正体会到了外祖父为什么那么珍爱墨梅图，从而理解梅花的品行，上升到中国人的气节。语文中低年级教学中，教师注重字形的书写字文的理解和区别运用，比如赵彤霞老师执教《植物妈妈有办法》一课，能在文中恰到好处的让学生理解“许多”和“许”“多”的区别，并用“纷纷”说一句话。又比如赵志芳执教《秋天的雨》一课中，注重了“爽”字的书写指导，教学中注重句子的训练，让学生练说比喻句。 3、注重学生情感态度和学习习惯的培养。 注重学生情感态度和学习习惯的培养是成为这次比赛课的又一亮点。老师们在教学中，做到自始至终关注学生的情感，营造宽松、民主、和谐的教学气氛，尊重每个学生，积极鼓励他们在学习中的尝试，保护他们的自尊心和积极性。比如吴蕊霞老师的鼓励具有个性化，激励性的语言常挂嘴边，成为学生不断学习、创新不可缺乏的精神动力。同时在教学中注重学习习惯的培养，比如高月枝老师在授课的同时适时对学生进行了课常规的教育，整个一节课，教学秩序井然有序，对于刚上学两个星期的孩子真的很难得。 4、善用多媒体教学。 本次讲课赛几乎所有的老师都制作了精美实用的多媒体课件，追求既生动形象又快捷高效的教学效果。特别是赵丽和龚伟科两位老师用我们上学期培训的知识制作了白板课件。 5、教师素养良好。 通过这次比赛，我们欣喜地看到我校青年教师具备良好的教师基本素质。他们教态大方得体，语言清晰，具有较强的亲和力和应变能力。王敏、陈蓉等老师她们在课堂上文雅得体的教态，丰富的肢体语言以及亲切和蔼的微笑，都给我们留下了深刻的印象，深受学生的喜爱。 针对本次讲课赛反映出的问题，给老师们提出以下建议，跟老师们商榷：1、语文教学中，略读课文的教学教师应大胆放手学生，让学生充分展示自己。有感情的朗读，重在先理解再
关于我的幸福作文八篇汇总 幸福在每个人的心中都不一样。在饥饿者的心中，幸福就是一碗香喷喷的米饭；在果农的心中，幸福就是望着果实慢慢成熟；在旅行者的心中，幸福就是游遍世界上的好山好水。而在我的心中，幸福就是每天快快乐乐，无忧无虑；幸福就是朋友之间互相帮助，互相关心；幸福就是在我生病时，母亲彻夜细心的照顾我。 幸福在世间上的每个角落都可以发现，只是需要你用心去感受而已。 记得有一次，我早上出门走得太匆忙了，忘记带昨天晚上准备好的钢笔。老师说了：“今天有写字课，必须要用钢笔写字，不能用水笔。”我只好到学校向同学借了。当我来到学校向我同桌借时，他却说：“我已经借别人了，你向别人借吧！”我又向后面的同学借，可他们总是找各种借口说：“我只带了一枝。”问了三四个人，都没有借到，而且还碰了一鼻子灰。正当我急的像热锅上的蚂蚁团团转时，她递给了我一枝钢笔，微笑的对我说：“拿去用吧！”我顿时感到自己是多么幸福！在我最困难的时候，当别人都不愿意帮助我的时候，她向我伸出了援手。 幸福也是无时无刻都在身旁。 当我生病的时候，高烧持续不退时，是妈妈在旁边细心
的照顾我，喂我吃药，甚至一夜寸步不离的守在我的床边，直到我苏醒。当我看见妈妈的眼睛布满血丝时，我的眼眶在不知不觉地湿润了。这时我便明白我有一个最疼爱我的妈妈，我是幸福的！ 幸福就是如此简单！不过，我们还是要珍惜眼前的幸福，还要给别人带来幸福，留心观察幸福。不要等幸福悄悄溜走了才发现，那就真的是后悔莫及了！ 这就是我拥有的幸福，你呢？ 悠扬的琴声从房间里飘出来，原来这是我在弹钢琴。优美的旋律加上我很强的音乐表现力让一旁姥爷听得如醉如痴。姥爷说我是幸福的，读了《建设幸福中国》我更加体会到了这一点。 儿时的姥爷很喜欢读书，但当时家里穷，据姥爷讲那时上学可不像现在。有点三天打鱼两天晒网，等地里农活忙了太姥爷就说：“别去念书了，干地里的活吧。”干活时都是牛马拉车，也没机器，效率特别低。还要给牲口拔草，喂草，拾柴火，看书都是抽空看。等农闲时才能背书包去学校，衣服更是老大穿了，打补丁老二再接着穿，只有盼到过年时才有能换上件粗布的新衣服。写字都是用石板，用一次擦一次，那时还没有电灯，爱学习的姥爷在昏暗的煤油灯下经常被灯火不是烧了眉毛就是燎了头发。没有电灯更没有电视，没有电视更没有见过钢琴，只知道钢琴是贵族家用的。
教师即兴演讲题目之63个话题 来源：思雨教育资源网|教学资源|课件论文|作文作者：无边思雨发表日期：2009-5-30 13:16:19 阅读次数： 910 查看权限：普通文章 1、如何维护班集体荣誉？ 2、如何看待学生时代早恋问题？ 3、成人与成才二者是怎样的关系？结合实例说明自己的观点。 4、不同地域、不同背景、不同习惯的同学之间该如何相处？ 5、怎样面对学习、生活中遇到的挫折？ 6、你最崇拜的人是谁？“名人”还是自己？ 7、你认为我们是否应有感恩之心？感恩于谁？ 8、你希望自己会是怎样一位老师？你会如何教育自己的学生？ 9、“言行、仪表”与个人的发展。 10、如今继续提倡“勤俭、节约”作风是否已过时？ 11、在各种资料、媒体中常讲张扬个性，你认为我们该张扬什么样的个性？ 12、三轮车工人方尚礼自己生活的如乞丐，却将自己蹬车收入的35万多元用来资助失学儿童，当病重时，社会捐助给他治病的钱，也被他捐给了希望工程。你对方尚礼的这种行为有何评述？ 13、电视广告不宜过多 14、保护环境是每个人的责任 15、我中学时代的一个朋友 16、世界需要热心肠 17、向权威挑战 18、2008年的我 19、我爱电视广告 20、我的母亲 21、尊重是孩子成长的基石 22、如何培养学生的好奇心 23、推广普通话 24、“恶语伤人六月寒” 25、我心中的偶像 26、假如我是画家 27、童年趣事 28、珍惜现在 29、我最爱看的电视节目 30、有人认为老师是不断燃烧的蜡烛，你认为呢？ 31、新课程背景下良好师生场的营造。 32、让谐趣幽默走进我们的课堂。 33、阅读教学中如何开展有效的对话教学？ 34、如何正确处理价值取向和个性化阅读的关系？ 35、新课程背景下一堂好课的标准是什么？ 36、“语文教学工具性与人文性统一”的内涵是什么？ 37、如何实践语文教学的人文性和工具性的“统一”？ 38、如何挖掘教材资源，准确选点，扎实训练？
小学生作文《感悟幸福》范文五篇 小草说,幸福就是大地增添一份绿意;阳光说,幸福就是撒向人间的温暖;甘露说,幸福就是滋润每一个生命。下面是为大家带来的有关幸福650字优秀范文，希望大家喜欢。 感悟幸福650字1 生活就像一部壮丽的交响曲，它是由一篇一篇的乐章组成的，有喜、有怒、有哀、有乐。每一个人都有自己丰富多彩的生活，我也有自己的生活。我原本以为，吃可口的牛排，打电脑游戏，和朋友开心玩乐就是幸福。可是，我错了，幸福并不仅仅如此。 记得有一次，我放学回到家里放下书包就拿起一包饼干来吃。吃着吃着，突然我觉得牙齿痛了起来，而且越来越痛，痛得我连饼干也咬不动了。我放下饼干，连忙去拿了一面镜子来看。原来这又是那一颗虫牙在“作怪”。“哎哟哟，哎哟哟，痛死我了……”我不停地说着。渐渐地，那牙疼得越来越厉害，疼得我坐立不安，直打滚。后来在妈妈的陪伴下去了医院，治好了那颗虫牙。跨出医院大门时，我觉得心情出奇的好，天空格外的蓝，路边的樟树特别的绿，看什么都顺眼，才猛然一悟，幸福是简单而平凡的，身体健康就是一种幸福! 这学期我发现我的英语退步了，我决定要把这门功课学好，于是，我每天回
家做完作业后，都抽出半小时时间复习英语，在课上也听得特别认真，一遇到不懂的题目主动请教老师。经过一段时间的努力，终于，在上次考试的时候，我考了97分。妈妈表扬了我，我心里美滋滋的。我明白了经过自己的努力享受到成功的喜悦，这也是一种幸福。 …… 每个人都无一例外的渴望幸福。不同的人有不同的感受，其实，幸福就是那种能在平凡中寻找欢乐、能在困境中找到自信的一种心境。同学们，幸福其实很简单，就在我们的身边，触手可及。用心去认真地品味吧，它一直未曾离开我们身边! 感悟幸福650字2 有的人认为幸福就是腰缠万贯，有的人认为幸福就是找到意中人，“采菊东篱下，悠然见南山”是陶渊明对邪恶幸福，“从明天起做一个幸福人，喂马、劈柴、周游世界。从明天起，关心蔬菜和粮食，我有一所房子，面朝大海，春暖花开。”这是海子的幸福。一千种人就有一千种对幸福的理解。 我对幸福的理解就是幸福使简单而平凡的，是无处不在的! 我的牙疼得奇怪而顽强不是这颗牙疼就是那颗牙疼;不是吃冷的疼就是吃热
关于以幸福为话题的作文800字记叙文5篇 ----WORD文档，下载后可编辑修改---- 下面是作者为各位家长学生收集整理的作文（日记、观后感等）范本，欢迎借鉴参考阅读，您的努力学习和创新是为了更美好的未来，欢迎下载！ 以幸福为话题的作文800字记叙文1： 那是我生病后的第三天，妈妈从早上五点就起来为我准备早点。她蹑手蹑脚地走着“针步”，下楼煮早点，“啪”的一声，妈妈打开了煤气。在拿肉丝，打鸡蛋的她全然不知我正躲在楼梯口“监视”着她的一举一动。不一会儿，蛋炒好了。 她开始切肉丝，一不小心，妈妈的手指切破皮了，鲜血正一滴一滴地流下来，为了不影响我的睡眠，她把手指放在嘴里吸了一下，坚持把剩下的肉丝切完。 此时的我，心中犹如打翻了五味瓶，眼里的泪像断了线的珍珠般掉了下来，我再也忍不住了，一个劲地冲到妈妈面前，她赶紧把手背了过去，生怕让我知道了什么。 她吃惊地问我：“妈妈太吵了，吵到你了?”“不，不，没有”她见我这么早起来就让我再回去补个觉。我关心地问：“妈，你的手没事吧?”她吱唔着说：“没事，擦破点皮，不碍事!”我仔细地帮她清洗了伤口，贴了一片创可贴。 吃饭时，妈妈一直地往我碗里夹肉，“孩子，病刚好，多吃点!”可是我见她始终都没吃一块肉。我也夹了两块放在她的碗里。“儿子懂事了，你自己快点吃吧!补身体要紧!”我冲她点点头笑了笑，“嗯。” 这就是幸福，一份简简单单的幸福!我祈祷这幸福能伴我成长。 以幸福为话题的作文800字记叙文2： 在我眼中，成长就是记录我们长大过程中一点一滴的小事情的，而幸福就在这点点滴滴中。 在我的成长记忆中，永不磨灭的是2017年11月的一天。妈妈要去云南，妈妈早上四点半要到指定地点集合，这么早，妈妈要两三点就起来，可是最近我咳嗽比较严重，所以天天给我煮萝卜汤喝。 “叮铃铃，叮铃铃”闹钟叫了起来，把我从睡梦中吵醒，一醒来，去找妈妈，
谈如何尊重人尊重他人，我们赢得友谊；尊重他人，我们收获真诚；尊重他人，我们自己也 获得尊重；相互尊重，我们的社会才会更加和谐. ——题记 尊重是对他人的肯定，是对对方的友好与宽容。它是友谊的润滑剂，它是和谐的调节器， 它是我们须臾不可脱离的清新空气。“主席敬酒，岂敢岂敢？”“尊老敬贤，应该应该！”共和 国领袖对自己老师虚怀若谷，这是尊重；面对许光平女士，共和国总理大方的叫了一 声“婶婶”，这种和蔼可亲也是尊重。 尊重不仅会让人心情愉悦呼吸平顺，还可以改变陌生或尖锐的关系，廉颇和蔺相如便是 如此。将相和故事千古流芳:廉颇对蔺相如不满，处处使难，但蔺相如心怀大局，对廉颇相 当的尊重，最后也赢得了廉颇的真诚心，两人结为好友，共辅赵王，令强秦拿赵国一点办法 也没有。蔺相如与廉颇的互相尊重，令得将相和的故事千百年令无数后人膜拜。 现在，给大家举几个例子。在美国，一个颇有名望的富商在散步 时，遇到一个瘦弱的摆地摊卖旧书的年轻人，他缩着身子在寒风中啃着发霉的面包。富 商怜悯地将8美元塞到年轻人手中，头也不回地走了。没走多远，富商忽又返回，从地摊上 捡了两本旧书，并说：“对不起，我忘了取书。其实，您和我一样也是商人！”两年后，富商 应邀参加一个慈善募捐会时，一位年轻书商紧握着他的手，感激地说：“我一直以为我这一生 只有摆摊乞讨的命运，直到你亲口对我说，我和你一样都是商人，这才使我树立了自尊和自 信，从而创造了今天的业绩??”不难想像，没有那一 句尊重鼓励的话，这位富商当初即使给年轻人再多钱，年轻人也断不会出现人生的巨变， 这就是尊重的力量啊 可见尊重的量是多吗大。大家是不是觉得一个故事不精彩，不够明确尊重的力量，那再 来看下一个故事吧！ 一家国际知名的大企业，在中国进行招聘，招聘的职位是该公司在中国的首席代表。经 过了异常激烈的竞争后，有五名年轻人，从几千名应聘者中脱颖而出。最后的胜出者，将是 这五个人中的一位。最后的考试是一场面试，考官们都 作文话题素材之为人处世篇：尊重 思路 人与人之间只有互相尊重才能友好相处 要让别人尊重自己，首先自己得尊重自己 尊重能减少人与人之间的摩擦 尊重需要理解和宽容 尊重也应坚持原则 尊重能促进社会成员之间的沟通 尊重别人的劳动成果 尊重能巩固友谊 尊重会使合作更愉快 和谐的社会需要彼此间的尊重 名言 施与人，但不要使对方有受施的感觉。帮助人，但给予对方最高的尊重。这是助人的艺 术，也是仁爱的情操。———刘墉 卑己而尊人是不好的，尊己而卑人也是不好的。———徐特立 知道他自己尊严的人，他就完全不能尊重别人的尊严。———席勒 真正伟大的人是不压制人也不受人压制的。———纪伯伦 草木是靠着上天的雨露滋长的，但是它们也敢仰望穹苍。———莎士比亚
最新整理高中关于幸福的议论文800字范文3篇 范文一 什么是幸福?当我把一个棒棒糖递给六岁的邻居小妹妹时，她满足的笑容告诉我，这是她的幸福。当我轻轻地走过妹妹的写字台时，我瞥见埋在桌上的妹妹的僵硬的表情。我笑笑，走近，她抬头，水汪汪的眼睛望着我，似乎带着某种渴求。我说：出去玩吧!她笑了，蹦蹦跳跳地跑了出去。我诧异，这么真诚的笑。玩耍是她的幸福。 暑假到了，马上面临实习的哥哥回来了。可没过几天，就不见人影了，好容易盼他回来，暑假也结束了。他说他去了内蒙的好多地方。我关切的问他累吗?他说：累啊!随后又骄傲地说：“可是我学会了许多东西，我相信那对我以后的人生路是有帮助的。”我笑，大声地喊：哥，你是我的榜样。在他看来，他的暑假是充实的，他是幸福的! 夜幕降临，繁星点点。隔着一层帘，我看见常年劳作的父亲坐在那里，默默地吸着一支烟。灯光打在他的脸上，我看不清他的表情，只有那斑白的鬓角依稀可见。父亲真的老了，每天早出晚归来支撑这个家，他一定很累了。眼泪盈满了眼眶，最后还是不争气的流了下来……“咳、、咳、、”一阵剧烈的咳嗽声传来。我擦干眼泪，走到父亲旁边，父亲把那支烟熄灭，慈祥的笑笑，说：爸爸老了，不中用了。我说：没有啊!父女两开怀的笑了，笑声混着一个个烟圈飘向远方……我问父亲：爸，这么多年付出，这么多年劳作，你幸福吗?他坚定地告诉我，幸福!他说：“只要你们开开心心快快乐乐地成长，我做的一切都值得。”他又说：“霞，好好读书，爸爸赚钱供你上大学，我还没老呢，至少还能干XX年，20年……然后是一片寂静，我和父亲看着远方，那里有希望。 年迈的姥姥是家里的大长辈，他常常念叨：平安就是福。那也许是经历了人生的酸甜苦辣后的感悟吧!每逢新春，一大家人在姥姥家围着看电视时，那应该是她的幸福吧! 幸福是什么?它不是你一个人拥有一座豪宅，它是一家人在并不宽敞的屋子里谈笑风生。它不是你一个人有拥山珍海味，它是一家人和和乐乐的吃一些普通
感受幸福作文(15篇) 感受幸福作文第1篇： 幸福是什么？这是许多同学要问的问题。 很小的时候，我就明白钱能够买来一大盒巧克力；钱能够买来玩具汽车；钱能够买许多的美丽的洋娃娃；钱能够买来一个大楼…… 我以为有钱就是幸福。 倡我错了，钱虽然能够买来一屋子巧克力，但买了甜蜜，钱虽然能买到房子，可是却买来家庭幸福；钱虽然能买来药，可是却买来健康，钱虽然能买来闹钟，可是买来时间……那时，我又明白了有钱必须幸福。 以前，我总是为了一条连衣裙而朝思暮想，盼望有一天能够穿上裙子，去放风筝。那时候，我以为拥有就是幸福。 最终有一天，妈妈给我买了这条连衣裙，我高兴的一宿都没有睡觉。可是几天的新鲜劲没有了，穿上裙子后，我并没有什么改变，依然是一个黄毛丫头。于是把它扔到箱子里。几个月后，我又把它翻出来，可是已经小了，穿下了。我又明白了，虽然裙子很美，但都是暂时的，完美的时光总是转瞬消失。 “幸福是什么？”我依然没有感受到。 几年后，我在街上看到了一对耄耋老人，他们虽然履蹒跚，可是互相搀扶，有时抬头看看天上的云卷云舒，有时望望西天如血的残阳，她们脸上洋溢着的是满足和幸福。 噢，我明白幸福就是真情。虽然他们很穷，可是他们很
相爱。他们彼此珍惜，从感叹世界对他们的公平。往往有的有钱人，他们虽然很有钱，可是他们并幸福，因为他们的心总是被金钱和权势所占据了，根本享受了这天伦之乐。 幸福其实很简单，就是和爸爸、妈妈吃一顿饭，和他在一齐聊聊天。 感受幸福作文第2篇： 夜，悄悄地打开了黑暗，散布着一如既往的宁静，天上的繁星披上了闪装，正对着我的眼，似乎害怕我听到它们之间的悄悄话。 知何时，甘寂寞的虫儿起劲地奏起了动听的乐曲，清凉的微风夹杂着泥土的芳香悄悄地将白天的烦闷与喧嚣赶跑。夜，显得更加宁静而诗意了。 静静的，左思，右想，就这样静静地坐在楼顶上，感受着夜馈赠我的美妙。就连天上偶尔飘过的云朵，也像是怕惊动了夜的宁静，如绒毛在平静水面滑过般，显得那么轻柔而迷人。 今夜独处在空旷的夜空下，感受着夜带给我的美妙，幸福惬意溢满于心。原先自我一向以来苦苦追寻的幸福其实就在自我的身边。 以往，有人努力打拼，渴望生活富裕来获得幸福，可一辈子的艰辛拼搏使自我逐渐沦为金钱的奴隶，苦苦追寻的幸福也越寻越远，最终留给自我的是岁月无情地染白的头发。其实，幸福并非是追寻能得到的，幸福是一种感受，仅有用心感受身边的一切，你就能发现，幸福无处在，譬如，管贫
青年教师朗诵比赛活动方案 （2014----2015）学年度下学期 一、活动目的： 学校是推广普通话，规范语言文字的主阵地，教师作为推广普通话的中坚力量有着不可忽视的重要作用。因此，为了加强教师基本功训练，提升教师的朗读水平，教导处根据语言文字规范化活动计划，开展以“朗读美文展我风采”的教师朗诵比赛。通过教师美文朗读比赛，提高我校青年教师普通话水平，营造浓厚的校园读书氛围，提升教师教学基本功，促使教师重视朗读教学，促进学生健康和谐发展。 二、活动组织：教导处 三、具体活动安排： 1、培训时间：6月8日（周一）下午14:30 2、比赛时间：6月15日（周一）下午14:30 3、比赛地点：四楼舞蹈室 4、参赛人员：35岁以下（含35岁）青年教师必须参加，同时欢迎35岁以上教师参加。 5、比赛内容：作品自选，体裁不限（不少于三分钟） 6、比赛形式：可配乐，参赛人员独立诵读。 7、评委：黄冬梅蒋丽丽郭艳华贺芳刘忠霞冷静武玉德 8、分数统计：王辉赵慧贤
9、主持：徐金凤 四、活动程序： 1、学校将在赛前一周邀请校长对参赛人员进行培训。 2、参赛教师提前十分钟到达比赛场地，做好准备工作。 3、14:40正式进行比赛，按抽签顺序进行。 4、评分办法：比赛采取现场评分的办法，满分10分，比赛结束后，进行分数汇总、统计，取平均分，宣布比赛成绩。 5、校长点评并作总结。 五、设奖情况： 本次比赛将设一等奖2名，二等奖3名，三等奖5名，优秀奖若干名。比赛成绩计入年末教师量化考核。 六、朗诵比赛评分标准 （一）、主题内容（2分） 1、内容（1分）：题材不限，内容健康向上；充实生动，有真情实意 2、主题（1分）：寓意深刻，富有感召力 （二）、普通话（3分） 1、发音（1分）：语音准确1分，较准确0.8分，基本准确0.5分，不准确不得分。 2、语速（1分）：语速恰当、声音洪亮，表达自然流畅1分，因不熟练，每停顿一次扣0.1分。
尊重他人的写作素材 导读：——学生最需要礼貌 著名数学家陈景润回厦门大学参加 60 周年校庆，向欢迎的人们说的第一句话是：“我非常高兴回到母校，我常常怀念老师。”被人誉为“懂得人的价值”的著名经济学家、厦门大学老校长王亚南，曾经给予陈景润无微不至的关心和帮助。陈景润重返母校，首先拜访这位老校长。校庆的第三天，陈景润又出现在向“哥德巴赫猜想”进军的启蒙老师李文清教授家中，陈景润非常尊重和感激他。他还把最新发表的数学论文敬送李教授审阅，并在论文扉页上工工整整写了以下的字：“非常感谢老师的长期指导和培养——您的学生陈景润。”陈景润还拜访了方德植教授，方教授望着成就斐然而有礼貌的学生，心里暖暖的。 ——最需要尊重的人是老师 周恩来少年时在沈阳东关模范学校读书期间 , 受到进步教师高盘之的较大影响。他常用的笔名“翔宇”就是高先生为他取的。周恩来参加革命后不忘师恩 , 曾在延安答外国记者问时说：“少年时代我在沈阳读书 , 得山东高盘之先生教诲与鼓励 , 对我是个很大的 促进。” 停奏抗议的反思 ——没有礼仪就没有尊重 孔祥东是著名的钢琴演奏家。 1998 年 6 月 6 日晚，他在汕头
举办个人钢琴独奏音乐会。演出之前，节目主持人再三强调，场内观众不要随意走动，关掉 BP 机、手提电话。然而，演出的过程中，这种令人遗憾的场面却屡屡发生：场内观众随意走动， BP 机、手提电话响声不绝，致使孔祥东情绪大受干扰。这种情况，在演奏舒曼作品时更甚。孔祥东只好停止演奏，静等剧场安静。然而，观众还误以为孔祥东是在渴望掌声，便报以雷鸣般的掌声。这件事，令孔祥东啼笑皆非。演出结束后，孔祥东说：有个 BP 机至少响了 8 次，观众在第一排来回走动，所以他只得以停奏抗议。 “礼遇”的动力 ——尊重可以让人奋发 日本的东芝公司是一家著名的大型企业，创业已经有 90 多年的历史，拥有员工 8 万多人。不过，东芝公司也曾一度陷入困境，土光敏夫就是在这个时候出任董事长的。他决心振兴企业，而秘密武器之一就是“礼遇”部属。身为偌大一个公司的董事长，他毫无架子，经常不带秘书，一个人步行到工厂车间与工人聊天，听取他们的意见。更妙的是，他常常提着酒瓶去慰劳职工，与他们共饮。对此，员工们开始都感到很吃惊，不知所措。渐渐地，员工们都愿意和他亲近，他赢得了公司上下的好评。他们认为，土光董事长和蔼可亲，有人情味，我们更应该努力，竭力效忠。因此，土光上任不久，公司的效益就大力提高，两年内就把亏损严重、日暮途穷的公司重新支撑起来，使东芝成为日本最优秀的公司之一。可见，礼，不仅是调节领导层之间关
感悟幸福(作文)(20篇) 篇一篇的乐章组成的，喜、怒、哀、乐。每一个人都自我丰富多彩的生活，我也自我的生活。我原本以为，吃可口的牛排，打电脑游戏，和朋友开心玩乐就是幸福。可是，我错了，幸福并不仅仅如此。 记得一次，我放学回到家里放下书包就拿起一包饼干来吃。吃着吃着，突然我觉得牙齿痛了起来，并且越来越痛，痛得我连饼干也咬不动了。我放下饼干，连忙去拿了一面镜子来看。原先这又是那一颗虫牙在“作怪”。“哎哟哟，哎哟哟，痛死我了”我不停地说着。渐渐地，那牙疼得越来越厉害，疼得我坐立不安，直打滚。之后在妈妈的陪伴下去了医院，治好了那颗虫牙。跨出医院大门时，我觉得心境出奇的好，天空格外的蓝，路边的樟树异常的绿，看什么都顺眼，才猛然一悟，幸福是简单而平凡的，身体健康就是一种幸福！ 这学期我发现我的英语退步了，我决定要把这门功课学好，于是，我每一天回家做完作业后，都抽出半小时时间复习英语，在课上也听得异常认真，一遇到不懂的题目主动请教教师。经过一段时间的努力，最终，在上次考试的时候，我考了97分。妈妈表扬了我，我心里美滋滋的。我明白了经过自我的努力享受到成功的喜悦，这也是一种幸福。
每个人都无一例外的渴望幸福。不一样的人不一样的感受，其实，幸福就是那种能在平凡中寻找欢乐、能在困境中找到自信的一种心境。同学们，幸福其实很简单，就在我们的身边，触手可及。用心去认真地品味吧，它一向未曾离开我们身边！ 感悟幸福(作文) 第8篇： 幸福无时没，幸福无处不在。儿时，你的幸福就是当你跌倒失声痛苦时，母亲抱起你，拍打着你背时的那句“别哭。”;成年时，你的幸福就是在你结婚时你身旁的那位拉起你的手问你的那句“你愿意吗”;老年时，你的幸福就是在椅子背后孙子的那句“奶奶我帮你敲背!”。家庭中，幸福是一家子的和乐融融;学校里，幸福是同学间的互相竞争;赛场上，幸福是队友间的默契配合。 然而，幸福不全然是唾手可得的，想不付出任何代价而得到幸福，那是神话。张志新说;“苦换来的是知识真理，坚持真理，就应自觉的欣然理解痛苦，那时，也仅那时，痛苦才将化为幸福。”仅心身遭受过痛苦的洗涤，幸福才会来到，痛得越深，苦得越彻，幸福得就越甜。鲁迅说：“穿掘到灵魂的深处，使人受了精神的苦刑而得到的创伤，又即从这得伤和养伤的愈合中，得到苦的涤除，而上了苏生的路。”从而得到了幸福的真谛。拉罗什夫科说过：“幸福后面是灾祸，灾祸后面是幸福。”你想成为幸福的人吗愿你首先吃得
青年教师基本功大赛即兴演讲题目【题目1】我的兴趣爱好【题目2】谈谈内心和谐【题目3】人最难超越的高度就是自己【题目4】我的价值观【题目5】谈谈与人相处【题目6】坚守心灵的一方沃土【题目7】给快乐找个理由【题目8】年轻 没有什么不可以【题目9】心底无私天地宽【题目10】人是需要一点精神的【题目11】我们与时代同行【题目12】生活从“心”开始【题目13】让更多的人快乐 【题目14】面对繁杂的教学工作 你如何调整心态 【题目15】和谐、健康、快乐【题目16】我喜爱的书刊【题目17】你如何发展自己的专业弱点【题目18】善待自己 呵护希望【题目18】.上公开课对一个教师的成长的作用【题目19】培养积极心态 感悟责任人生【题目24】永不言弃 我心永恒 准备时间 3分钟 【题目25】.你怎样做个身心健康的老师【题目26】你如何看待家长满意工程 【题目27】新课程执行过程中 你碰到最棘手的问题是什么【题目28】课堂教学中 你最关注的是什么【题目29】你希望学校领导关心青年教师哪些方面【题目30】谈谈自己的业余生活【题目31】简评最近的工作情况。【题目32】怎样才能提高教师的凝聚力。【题目33】.谈谈做班主任的心得【题目34】.你怎样定义教师【题目35】简介杨森中学【题目36】.点评一位我校的优秀教师【题目37】.如何看待家长的不理解【题目38】.谈谈卫生与健康【题目39】谈谈我校的环境. 【题目40】谈谈如何管理学生【题目41】谈谈你对职业道德的认识【题目42】我参加校本研修之感想。【题目43】“依法治教 注重服务 着力塑造行业形象” 请你谈谈你的设想【题目44】.如何发挥你校师生之特长 【题目45】.怎样调动老师的工作积极性 【题目46】.谈谈你对校本教研的看法。【题目47】.我是怎样备课的。【题目48】.维持校门口的秩序 我的一点想法。【题目49】如何丰富教师的业余生活 缓解教师的心理压力 【题目50】谈谈你对节日文化的认识【题目51】学校活动很多的情况下 你如何调节自己的心态 【题目52】德育倡导“全面德育 全员德育” 请你谈谈自己的理解。【题目53】如何让家长尊重教师 【题目54】你认为提高教育质量应从哪里抓起【题目55】从哪些方面帮助班主任管理学生篇二：教师即兴演讲题目之63个话题 教师即兴演讲题目之63个话题 来源：思雨教育资源网|教学资源|课件论文|作文作者：无边思雨发表日期：2009-5-30 13:16:19 阅读次数： 910 查看权限：普通文章 1、如何维护班集体荣誉？ 2、如何看待学生时代早恋问题？ 3、成人与成才二者是怎样的关系？结合实例说明自己的观点。 4、不同地域、不同背景、不同习惯的同学之间该如何相处？ 5、怎样面对学习、生活中遇到的挫折？ 6、你最崇拜的人是谁？“名人”还是自己？ 7、你认为我们是否应有感恩之心？感恩于谁？ 8、你希望自己会是怎样一位老师？你会如何教育自己的学生？ 9、“言行、仪表”与个人的发展。 10、如今继续提倡“勤俭、节约”作风是否已过时？ 11、在各种资料、媒体中常讲张扬个性，你认为我们该张扬什么样的个性？ 12、三轮车工人方尚礼自己生活的如乞丐，却将自己蹬车收入的35万多元用来资助失学儿童，当病重时，社会捐助给他治病的钱，也被他捐给了希望工程。你对方尚礼的这种行为有何评述？ 13、电视广告不宜过多 14、保护环境是每个人的责任
尊重_议论文素材 "礼遇"的动力 --尊重可以让人奋发 日本的东芝公司是一家著名的大型企业，创业已经有90 多年的历史，拥有员工8 万多人。不过，东芝公司也曾一度陷入困境，土光敏夫就是在这个时候出任董事长的。他决心振兴企业，而秘密武器之一就是"礼遇"部属。身为偌大一个公司的董事长，他毫无架子，经常不带秘书，一个人步行到工厂车间与工人聊天，听取他们的意见。更妙的是，他常常提着酒瓶去慰劳职工，与他们共饮。对此，员工们开始都感到很吃惊，不知所措。渐渐地，员工们都愿意和他亲近，他赢得了公司上下的好评。他们认为，土光董事长和蔼可亲，有人情味，我们更应该努力，竭力效忠。因此，土光上任不久，公司的效益就大力提高，两年内就把亏损严重、日暮途穷的公司重新支撑起来，使东芝成为日本最优秀的公司之一。可见，礼，不仅是调节领导层之间关系的纽带，也是调节上下级之间关系，甚至和一线工人之间关系的纽带。世界知识产权日 --尊重知识 在2000 年10 月召开的世界知识产权组织第35 届成员国大会上，我国提议将 4 月26 日定为"世界知识产权日"。这个提案经世界知识产权组织成员国大会得到了确定。2001 年4 月26 日成为第一个"世界知识产权日"。这是我国尊重知识的具体表现。 屠格涅夫与乞丐 --尊重比金钱更重要 俄罗斯文豪屠格涅夫一日在镇上散步，路边有一个乞丐伸手向他讨钱。他很想有所施与，从口袋掏钱时才知道没有带钱袋。见乞丐的手伸得高高地等着，屠格涅夫面有愧色，只好握着乞丐的手说："对不起，我忘了带钱出来。"乞丐笑了，含泪说："不，我宁愿接受您的握手。" 孙中山尊重护士 --尊重不分社会地位 有一天，孙中山先生病了，住院治疗。当时，孙中山已是大总统、大元帅了。但是，他对医务人员很尊重，对他们讲话很谦逊。平时，无论是早晨或是晚间，每当接到护士送来的药品，他总是微笑着说声"谢谢您"，敬诚之意溢于言辞。 1925 年孙中山患肝癌，弥留之际，当一位护理人员为他搬掉炕桌时，孙中山先生安详地望着她，慈祥地说："谢谢您，您的工作太辛苦了，过后您应该好好休息休息，这阵子您太辛苦了! "听了这话，在场的人都泣不成声。 毛泽东敬酒 --敬老尊贤是一种美德 1959 年6 月25 日，毛泽东回到离别30 多年的故乡韶山后，请韶山老人毛禹珠来吃饭，并特地向他敬酒。毛禹珠老人说："主席敬酒，岂敢岂敢! "毛泽东接着说："敬老尊贤，应该应该。" 周恩来不穿拖鞋接待外宾 --衣着整齐体现对人的尊重 周恩来晚年病得很重，由于工作的需要，他还要经常接待外宾。后来，他病得连脚都肿起来了，原先的皮鞋、布鞋都不能穿，他只能穿着拖鞋走路，可是，有些重要的外事活动，他还是坚持参加。他身边的工作人员出于对总理的爱护和关心，对他说："您就穿着拖鞋接待外
关于尊重的论点和论据素材 关于尊重的论点 1.尊重需要理解和宽容。 2.尊重也应该坚持原则。 3.尊重知识是社会进步的表现。 4.尊重别人就要尊重别人的劳动。 5.尊重人才是社会发展的需要。 6.人与人之间需要相互尊重。 7.只有尊重别人才会受到别人的尊重。 8.尊重能促进人与人之间的沟通。 9.我们应该养成尊重他人的习惯。 10.对人尊重，常会产生意想不到的善果。 关于尊重的名言 1.仁者必敬人。《荀子》 2.忍辱偷生的人决不会受人尊重。高乃依 3.尊重别人的人不应该谈自己。高尔基 4.尊重别人，才能让人尊敬。笛卡尔 5.谁自尊，谁就会得到尊重。巴尔扎克 6.君子贵人而贱己，先人而后己。《礼记》 7.卑己而尊人是不好的，尊己而卑人也是不好的。徐特立 8.对人不尊敬，首先就是对自己的不尊敬。惠特曼
9.为人粗鲁意味着忘记了自己的尊严。车尔尼雪夫斯基 10.对人不尊敬的人，首先就是对自己不尊重。陀思妥耶夫斯基 11.对于应尊重的事物，我们应当或是缄默不语，或是大加称颂。尼采 12.尊重老师是我们中华民族的传统美德，我们每一个人都不应该忘记。xx 13.尊重劳动、尊重知识、尊重人才、尊重创造。《xx 大报告》 14.对别人的意见要表示尊重。千万别说：你错了。卡耐基 15.尊重人才，培养人才，是通用电器长久不败的法宝。杰克韦尔奇 16.君子之于人也，当于有过中求无过，不当于无过中求有过。程颐 17.施与人，但不要使对方有受施的感觉。帮助人，但给予对方最高的尊重。这是助人的艺术，也是仁爱的情操。刘墉 18.要尊重每一个人，不论他是何等的卑微与可笑。要记住活在每个人身上的是和你我相同的性灵。叔本华 19.要喜欢我们所不尊重的人是很难的;但要喜欢
感受幸福作文范文5篇 幸福是一种心灵的振颤。它像会倾听音乐的耳朵一样，需要不断地训练。下面给大家了感受幸福范文5篇，仅供参考。 我曾经填了一份读者反馈表，得了个二等奖，奖品是三百元钱。拿着那张三百元汇款单回家，我却不大开心。在路上，我想起了从前看过的一部电影，片名好像是《小鞋子》。 主人公小阿里在参加比赛时，一心只想跑第三名，以拿到梦寐以求的奖品——一双小鞋子。他想让妹妹穿着它，而不是光着脚去上学。 他被别人推倒了又爬起来再跑，情急之下，竟然冲到了第一名。 老师欣喜若狂地祝贺他，主办单位安排大官和他合影，阿里却难过地流下了眼泪。 尽管冠军有着很高的荣誉，能得到更为丰富的奖品，但那不是阿里最需要的，他需要那双并不漂亮的小鞋子。结果，他不仅没有得到，反而连仅有的一双鞋子也跑坏了。
在那个时候，我们或许可以这样解释幸福：幸福就是得到你急需的东西。 一个吃斋念佛的饥饿的人，面对着驰名中外的北京烤鸭，是不会有幸福感的，因为那不是他需要的，他急需的，可能只是两个馒头，一盘素炒豆芽而已；独自住在乡下的老人，总是能收到城里儿子寄来的钱物，很让乡亲们羡慕，但老人最想要的不是这些，而是儿孙膝下承欢的天伦之乐；在炎炎烈日下赶路的人，急需的是一片树阴，一阵凉风；一把扇子，一眼清凉的泉水，而不是一件名贵的貂皮大衣；大海是富饶的，它哺育了各种各样的生物，珍藏着无数的宝藏和财富。但在海上迷航的人，急需的却是普普通通的淡水。 聪明的你，可能已经猜到， ___不开心了。是的，我不需要三百元钱，钱我家里人会给我。我原本只想得个三等奖，三等奖的奖品是一百元钱。我想留为己用，不想让家里人知道。尽管这样做很不合理，但我还是想，因为我想。 幸福，是团聚；是分享快乐；是帮助他人；是朋友团结互助；是一个美梦；是……幸福无处不在，只要用心体会，就能感受到幸福的存在。
教师基本功是教师从事教育教学工作必须具备的最基本的职业技能。它包括通用于所有教师的一般基本功，也包括学科教学和教育工作的基本功。教师基本功是加强青年教师职业道德建设的一项重要内容，也是教师从事教育教学工作必须具备的最基本的职业技能。如果说教学是技术加艺术，那么这种技术和艺术主要表现在教师课堂教学的基本功上面。它是教师素质的重要表现，也是教学成败的关键。过去所说的教师基本功，无非是三字一画（钢笔、毛笔、粉笔字和简笔画）和语文基础知识、口头表达能力等，再加上一些专业学科的基本功（音乐、体育、美术等）。在新一轮的课程改革中，需要我们重新看待教师的教学基本功。随着时代的发展，教师基本功的含义越来越广，教 师基本功包括的范围越来越大。下面我谈谈自己对教师应该具备的基本功的认识。 一、为人师表教师基本功应以德为先，教师的基本素质首当其冲的是师德素质。 我认为教师首先要有高尚的师德，只有思想上以学生为本，有做名师的愿望，至少有一个积极健康的心态，才能练好基本功。 1、有理想，有事业心。 2、以身作则学校无小事，处处皆教育，教师一言一行都会对学生造成影响。 二、爱的能力教师做的是人的工作，应该有人文素质，在爱
人过程中进行教育教学工作。爱学生也是一种技能，爱他们，使他们 容易、愉悦接受。 三、表达能力. 1、语言表达普通话是教师的职业语言，教师能用普通话进 行教学，普通话一般应达到国家语委制定的《普通话水平测试》二级水平。 2、文字表达教师的工作比较繁重，但是要学会反思和总结， 把心得体会写出来，才能少走弯路，更快进步，摆脱烦琐；才能轻松、高效的工作。 四、动手能力. 1、三笔一画这是传统意义的教师基本功。 2、板书板书不仅表现出一位教师上课的基本功，而且也体现教师的教学态度乃至性格。 3、运用、制作教具使用、制作教具方面，能按教学要求，正确使用教具；能就地取材，制作简易的教具。 4、现代信息技术的掌握和运用。 5、演示一般教师的演示指教态，教师也要做一个演员。 五、备课能力
关于学会尊重的高中作文1000字以上 尊重是一杯清茶，只有真正懂它的人才能忽略它的寡淡，品出它深处的热烈。下面橙子为大家搜集整理有关学会尊重的高中作文，希望可以帮助到大家! 高中作文学会尊重曾经听说这样一个故事： 一位商人看到一个衣衫破烂的铅笔推销员，顿生一股怜悯之情。他不假思索地将10元钱塞到卖铅笔人的手中，然后头也不回地走开了。走了没几步，他忽然觉得这样做不妥，于是连忙返回来，并抱歉地解释说自己忘了取笔，希望不要介意。最后，他郑重其事地说：“您和我一样，都是商人。” 一年之后，在一个商贾云集、热烈隆重的社交场合，一位西装革履、风度翩翩的推销商迎上这位商人，不无感激地自我介绍道：“您可能早已忘记我了，而我也不知道您的名字，但我永远不会忘记您。您就是那位重新给了我自尊和自信的人。我一直觉得自己是个推销铅笔的乞丐，直到您亲口对我说，我和您一样都是商人为止。” 没想到商人这么—句简简单单的话，竟使一个不无自卑的人顿然树立起自尊，使—个处境窘迫的人重新找回了自信。正是有了这种自尊与自信，才使他看到了自己的价值和优势，终于通过努力获得了成功。不难想象，倘若当初没有那么—句尊重鼓励的话，纵然给他几千元也无济于事，断不会出现从自认乞丐到自信自强的巨变，这就是尊1 / 7
重，这就是尊重的力量! 尊重，是—种修养，一种品格，一种对别人不卑不亢的平等相待，一种对他人人格与价值的的充分肯定。任何人都不可能尽善尽美，完美无缺，我们没有理由以高山仰止的目光审视别人，也没有资格用不屑一顾的神情去嘲笑他人。假如别人在某些方面不如自己，我们不能用傲慢和不敬去伤害别人的自尊;假如自己在有些地方不如他人，我们不必以自卑或嫉妒去代替理应有的尊重。一个真正懂得尊重别人的人，必然会以平等的心态、平常的心情、平静的心境，去面对所有事业上的强者与弱者、所有生活中的幸运者与不幸者。 尊重是一缕春风，一泓清泉，一颗给人温暖的舒心丸，一剂催人奋进的强心剂。它常常与真诚、谦逊、宽容、赞赏、善良、友爱相得益彰，与虚伪、狂妄、苛刻、嘲讽、凶恶、势利水火不容。给成功的人以尊重，表明了自己对别人成功的敬佩、赞美与追求;表明了自己对别人失败后的同情、安慰与鼓励。只有要尊重在，就有人间的真情在，就有未来的希望在，就有成功后的继续奋进，就有失败后的东山再起。 尊重不是盲目的崇拜，更不是肉麻的吹捧;不是没有原则的廉价逢迎，更不是没有自卑的低三下四。懂得了尊重别人的重要，并不等于学会了如何尊重别人，从这个意义上说，尊重他人也是一门学问，学会了尊重他人，就学会了尊重自己，也就学会和掌握了人生的一大要义。 2 / 7