search for: search1

...emplate::Error (undefined method `model_name'' for NilClass:Class): 1: <%= form_for(@employee) do |e| %> 2: EMP ID<%= e.text_field :id %><br> 3: <%= e.submit ''search'', :controller => ''employees'', :action => ''search1'' %> 4: <% end %> in my search action i dint provide anything like def search end if i use <%= form_for(:employee) do |e| %> it shows no error but the data is moving in to my "show" action could any one provide me a soultion ? -- You received this messa...

...rbinom(N,1,0.5)), ncol=3) start<-(-1) end<-3 step<-10^(-2) n.steps<-(end-start)/step steps2 <-n.steps^2 grids<-seq(from=start+step, to=end, by=step) xMax <-matrix(0,N*steps2,3) xMax[,1]<-rep(x[,1],steps2) xMax[,2]<-rep(x[,2],steps2) xMax[,3]<-rep(x[,3],steps2) G.search1<-as.matrix(rep(grids, n.steps, each=N)) G.search2<-as.matrix(rep(grids, N, each=n.steps)) G.search<-cbind(1,G.search1, G.search2) Thank you Dimitris -- View this message in context: http://r.789695.n4.nabble.com/memory-problem-Error-cannot-allocate-vector-of-size-915-5-Mb-tp3707943p37...

...nd solr replication is quite complicated process and rollback or master-slave switch in this case is non-trivial task, that may have result in whole dataset inconsistency. Do you have any experience in such cases ? Maby load-balance in HAProxy colud do the thing ? Something like: ......... server search1 192.168.1.1:8983 check port 8983 inter 20s fastinter 2 server search2 192.168.1.2:8983 backup ......... Best Regards

...tTestSuite(path, litConfig, testSuiteCache) > File "M:\Development\Source\LLVM\utils\lit\lit\main.py", line 199, in getTestSuite > ts, relative = search(item) > File "M:\Development\Source\LLVM\utils\lit\lit\main.py", line 183, in search > cache[path] = res = search1(path) > File "M:\Development\Source\LLVM\utils\lit\lit\main.py", line 174, in search1 > cfg = TestingConfig.frompath(cfgpath, None, litConfig, mustExist = True) > File "M:\Development\Source\LLVM\utils\lit\lit\TestingConfig.py", line 44, in frompath > exec f...

...-started-with-xapian.readthedocs.org/en/latest/overview.html#datasets-and-example-code). The following are the steps that I have performed.: - Checked out the code at https://github.com/xapian/xapian-docsprint - - python index1.py ../../data/states.csv index1_states.py.db - - python search1.py index1_states.py.db/ Montana However I am getting the following output: INFO:xapian.search:'Montana'[0:10] = Could you please help me with what I am missing or doing wrong because I am not able to find the actual matches for Montana that is present in data/states.csv Thanks Shiv -----...

...provided a contrived example in the Appendix which demonstrates the code generated for both approaches. The key differences are highlighted inline. Evaluation In this section, we present an in-depth evaluation of the impact on clang bootstrap and summary results for two google internal workloads, Search1 and Search2 as well overall results on the SPECInt 2017 benchmarks. All experiments are conducted on Intel Skylake based systems unless otherwise noted. Profile guided optimizations using instrumented profiles are enabled for all builds. clang-bootstrap We pick 500 compiler invocations from a boo...

...provided a contrived example in the Appendix which demonstrates the code generated for both approaches. The key differences are highlighted inline. Evaluation In this section, we present an in-depth evaluation of the impact on clang bootstrap and summary results for two google internal workloads, Search1 and Search2 as well overall results on the SPECInt 2017 benchmarks. All experiments are conducted on Intel Skylake based systems unless otherwise noted. Profile guided optimizations using instrumented profiles are enabled for all builds. clang-bootstrap We pick 500 compiler invocations from a bo...

...es >> the code generated for both approaches. The key differences are highlighted >> inline. >> >> Evaluation >> >> In this section, we present an in-depth evaluation of the impact on clang >> bootstrap and summary results for two google internal workloads, Search1 >> and Search2 as well overall results on the SPECInt 2017 benchmarks. All >> experiments are conducted on Intel Skylake based systems unless otherwise >> noted. Profile guided optimizations using instrumented profiles are enabled >> for all builds. >> >> clang-b...

...y. > Great, thanks for confirming! Would you be willing to share specific numbers, how significant is the reduction in memory with jemalloc for clang? We double-checked our numbers with the larger benchmarks and we can confirm they were *not built with labels*. One of our large benchmarks, search1, is about 5 times the size of clang in terms of text size as reported by size command, and we are seeing a 70G memory overhead on this. Do you have data on the memory consumption of BOLT with larger benchmarks with jemalloc. We are trying to build Chrome with latest BOLT so that we can share the...

...ks for confirming! Would you be willing to share specific > numbers, how significant is the reduction in memory with jemalloc for > clang? We double-checked our numbers with the larger benchmarks and we > can confirm they were *not built with labels*. One of our > large benchmarks, search1, is about 5 times the size of clang in terms of > text size as reported by size command, and we are seeing a 70G memory > overhead on this. Do you have data on the memory consumption of BOLT with > larger benchmarks with jemalloc. We are trying to build Chrome with > latest BOLT so t...

Hello Maksim, On Wed, Oct 16, 2019 at 3:52 PM Maksim Panchenko <maks at fb.com> wrote: > Hi Sri, > > > > I want to clarify one thing before sending a detailed reply: did you > evaluate > > BOLT on Clang built with basic block sections? > In the makefile you reference, > > there are two versions: a “vanilla” and a default built with function > sections.

Greetings, We, at Google, recently evaluated Facebook’s BOLT, a Post Link Optimizer framework, on large google benchmarks and noticed that it improves key performance metrics of these benchmarks by 2% to 6%, which is pretty impressive as this is over and above a baseline binaryalready heavily optimized with ThinLTO + PGO. Furthermore, BOLT is also able to improve the performance of binaries