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doc/papers/concurrency/Paper.tex
rfd2f4a9 r016b1eb 224 224 {} 225 225 \lstnewenvironment{C++}[1][] % use C++ style 226 {\lstset{language=C++,moredelim=**[is][\protect\color{red}]{`}{`} }\lstset{#1}}226 {\lstset{language=C++,moredelim=**[is][\protect\color{red}]{`}{`},#1}\lstset{#1}} 227 227 {} 228 228 \lstnewenvironment{uC++}[1][] 229 {\lstset{language=uC++,moredelim=**[is][\protect\color{red}]{`}{`} }\lstset{#1}}229 {\lstset{language=uC++,moredelim=**[is][\protect\color{red}]{`}{`},#1}\lstset{#1}} 230 230 {} 231 231 \lstnewenvironment{Go}[1][] 232 {\lstset{language=Golang,moredelim=**[is][\protect\color{red}]{`}{`} }\lstset{#1}}232 {\lstset{language=Golang,moredelim=**[is][\protect\color{red}]{`}{`},#1}\lstset{#1}} 233 233 {} 234 234 \lstnewenvironment{python}[1][] 235 {\lstset{language=python,moredelim=**[is][\protect\color{red}]{`}{`} }\lstset{#1}}235 {\lstset{language=python,moredelim=**[is][\protect\color{red}]{`}{`},#1}\lstset{#1}} 236 236 {} 237 237 \lstnewenvironment{java}[1][] 238 {\lstset{language=java,moredelim=**[is][\protect\color{red}]{`}{`} }\lstset{#1}}238 {\lstset{language=java,moredelim=**[is][\protect\color{red}]{`}{`},#1}\lstset{#1}} 239 239 {} 240 240 … … 284 284 285 285 \begin{document} 286 %\linenumbers % comment out to turn off line numbering286 \linenumbers % comment out to turn off line numbering 287 287 288 288 \maketitle … … 450 450 \hline 451 451 stateful & thread & \multicolumn{1}{c|}{No} & \multicolumn{1}{c}{Yes} \\ 452 \hline 453 \hline 452 \hline 453 \hline 454 454 No & No & \textbf{1}\ \ \ @struct@ & \textbf{2}\ \ \ @mutex@ @struct@ \\ 455 \hline 455 \hline 456 456 Yes (stackless) & No & \textbf{3}\ \ \ @generator@ & \textbf{4}\ \ \ @mutex@ @generator@ \\ 457 \hline 457 \hline 458 458 Yes (stackful) & No & \textbf{5}\ \ \ @coroutine@ & \textbf{6}\ \ \ @mutex@ @coroutine@ \\ 459 \hline 459 \hline 460 460 No & Yes & \textbf{7}\ \ \ {\color{red}rejected} & \textbf{8}\ \ \ {\color{red}rejected} \\ 461 \hline 461 \hline 462 462 Yes (stackless) & Yes & \textbf{9}\ \ \ {\color{red}rejected} & \textbf{10}\ \ \ {\color{red}rejected} \\ 463 \hline 463 \hline 464 464 Yes (stackful) & Yes & \textbf{11}\ \ \ @thread@ & \textbf{12}\ \ @mutex@ @thread@ \\ 465 465 \end{tabular} … … 2896 2896 \label{s:RuntimeStructureCluster} 2897 2897 2898 A \newterm{cluster} is a collection of user and kernel threads, where the kernel threads run the user threads from the cluster's ready queue, and the operating system runs the kernel threads on the processors from its ready queue ~\cite{Buhr90a}.2898 A \newterm{cluster} is a collection of user and kernel threads, where the kernel threads run the user threads from the cluster's ready queue, and the operating system runs the kernel threads on the processors from its ready queue. 2899 2899 The term \newterm{virtual processor} is introduced as a synonym for kernel thread to disambiguate between user and kernel thread. 2900 2900 From the language perspective, a virtual processor is an actual processor (core). … … 2992 2992 \end{cfa} 2993 2993 where CPU time in nanoseconds is from the appropriate language clock. 2994 Each benchmark is performed @N@ times, where @N@ is selected so the benchmark runs in the range of 2--20 seconds for the specific programming language; 2995 each @N@ appears after the experiment name in the following tables. 2994 Each benchmark is performed @N@ times, where @N@ is selected so the benchmark runs in the range of 2--20 seconds for the specific programming language. 2996 2995 The total time is divided by @N@ to obtain the average time for a benchmark. 2997 2996 Each benchmark experiment is run 13 times and the average appears in the table. 2998 For languages with a runtime JIT (Java, Node.js, Python), a single half-hour long experiment is run to check stability;2999 all long-experiment results are statistically equivalent, \ie median/average/standard-deviation correlate with the short-experiment results, indicating the short experiments reached a steady state.3000 2997 All omitted tests for other languages are functionally identical to the \CFA tests and available online~\cite{CforallConcurrentBenchmarks}. 2998 % tar --exclude-ignore=exclude -cvhf benchmark.tar benchmark 2999 % cp -p benchmark.tar /u/cforall/public_html/doc/concurrent_benchmark.tar 3001 3000 3002 3001 \paragraph{Creation} … … 3007 3006 3008 3007 \begin{multicols}{2} 3009 \begin{cfa}[xleftmargin=0pt] 3010 `coroutine` MyCoroutine {}; 3008 \lstset{language=CFA,moredelim=**[is][\color{red}]{@}{@},deletedelim=**[is][]{`}{`}} 3009 \begin{cfa} 3010 @coroutine@ MyCoroutine {}; 3011 3011 void ?{}( MyCoroutine & this ) { 3012 3012 #ifdef EAGER … … 3016 3016 void main( MyCoroutine & ) {} 3017 3017 int main() { 3018 BENCH( for ( N ) { `MyCoroutine c;`} )3018 BENCH( for ( N ) { @MyCoroutine c;@ } ) 3019 3019 sout | result; 3020 3020 } … … 3030 3030 3031 3031 \begin{tabular}[t]{@{}r*{3}{D{.}{.}{5.2}}@{}} 3032 \multicolumn{1}{@{}r}{N\hspace*{10pt}} & \multicolumn{1}{c}{Median} & \multicolumn{1}{c}{Average} & \multicolumn{1}{c@{}}{Std Dev} \\ 3033 \CFA generator (1B) & 0.6 & 0.6 & 0.0 \\ 3034 \CFA coroutine lazy (100M) & 13.4 & 13.1 & 0.5 \\ 3035 \CFA coroutine eager (10M) & 144.7 & 143.9 & 1.5 \\ 3036 \CFA thread (10M) & 466.4 & 468.0 & 11.3 \\ 3037 \uC coroutine (10M) & 155.6 & 155.7 & 1.7 \\ 3038 \uC thread (10M) & 523.4 & 523.9 & 7.7 \\ 3039 Python generator (10M) & 123.2 & 124.3 & 4.1 \\ 3040 Node.js generator (10M) & 33.4 & 33.5 & 0.3 \\ 3041 Goroutine thread (10M) & 751.0 & 750.5 & 3.1 \\ 3042 Rust tokio thread (10M) & 1860.0 & 1881.1 & 37.6 \\ 3043 Rust thread (250K) & 53801.0 & 53896.8 & 274.9 \\ 3044 Java thread (250K) & 119256.0 & 119679.2 & 2244.0 \\ 3045 % Java thread (1 000 000) & 123100.0 & 123052.5 & 751.6 \\ 3046 Pthreads thread (250K) & 31465.5 & 31419.5 & 140.4 3032 \multicolumn{1}{@{}c}{} & \multicolumn{1}{c}{Median} & \multicolumn{1}{c}{Average} & \multicolumn{1}{c@{}}{Std Dev} \\ 3033 \CFA generator & 0.6 & 0.6 & 0.0 \\ 3034 \CFA coroutine lazy & 13.4 & 13.1 & 0.5 \\ 3035 \CFA coroutine eager & 144.7 & 143.9 & 1.5 \\ 3036 \CFA thread & 466.4 & 468.0 & 11.3 \\ 3037 \uC coroutine & 155.6 & 155.7 & 1.7 \\ 3038 \uC thread & 523.4 & 523.9 & 7.7 \\ 3039 Python generator & 123.2 & 124.3 & 4.1 \\ 3040 Node.js generator & 33.4 & 33.5 & 0.3 \\ 3041 Goroutine thread & 751.0 & 750.5 & 3.1 \\ 3042 Rust tokio thread & 1860.0 & 1881.1 & 37.6 \\ 3043 Rust thread & 53801.0 & 53896.8 & 274.9 \\ 3044 Java thread & 120274.0 & 120722.9 & 2356.7 \\ 3045 Pthreads thread & 31465.5 & 31419.5 & 140.4 3047 3046 \end{tabular} 3048 3047 \end{multicols} … … 3053 3052 Internal scheduling is measured using a cycle of two threads signalling and waiting. 3054 3053 Figure~\ref{f:schedint} shows the code for \CFA, with results in Table~\ref{t:schedint}. 3055 Note, the \CFA incremental cost for bulk acquire is a fixed cost for small numbers of mutex objects. 3056 User-level threading has one kernel thread, eliminating contention between the threads (direct handoff of the kernel thread). 3057 Kernel-level threading has two kernel threads allowing some contention. 3054 Note, the incremental cost of bulk acquire for \CFA, which is largely a fixed cost for small numbers of mutex objects. 3055 Java scheduling is significantly greater because the benchmark explicitly creates multiple threads in order to prevent the JIT from making the program sequential, \ie removing all locking. 3058 3056 3059 3057 \begin{multicols}{2} 3060 \ setlength{\tabcolsep}{3pt}3061 \begin{cfa} [xleftmargin=0pt]3058 \lstset{language=CFA,moredelim=**[is][\color{red}]{@}{@},deletedelim=**[is][]{`}{`}} 3059 \begin{cfa} 3062 3060 volatile int go = 0; 3063 `condition c;` 3064 `monitor`M {} m1/*, m2, m3, m4*/;3065 void call( M & `mutex p1/*, p2, p3, p4*/`) {3066 `signal( c );`3067 } 3068 void wait( M & `mutex p1/*, p2, p3, p4*/`) {3061 @condition c;@ 3062 @monitor@ M {} m1/*, m2, m3, m4*/; 3063 void call( M & @mutex p1/*, p2, p3, p4*/@ ) { 3064 @signal( c );@ 3065 } 3066 void wait( M & @mutex p1/*, p2, p3, p4*/@ ) { 3069 3067 go = 1; // continue other thread 3070 for ( N ) { `wait( c );`} );3068 for ( N ) { @wait( c );@ } ); 3071 3069 } 3072 3070 thread T {}; … … 3093 3091 3094 3092 \begin{tabular}{@{}r*{3}{D{.}{.}{5.2}}@{}} 3095 \multicolumn{1}{@{}r}{N\hspace*{10pt}} & \multicolumn{1}{c}{Median} & \multicolumn{1}{c}{Average} & \multicolumn{1}{c@{}}{Std Dev} \\ 3096 \CFA @signal@, 1 monitor (10M) & 364.4 & 364.2 & 4.4 \\ 3097 \CFA @signal@, 2 monitor (10M) & 484.4 & 483.9 & 8.8 \\ 3098 \CFA @signal@, 4 monitor (10M) & 709.1 & 707.7 & 15.0 \\ 3099 \uC @signal@ monitor (10M) & 328.3 & 327.4 & 2.4 \\ 3100 Rust cond. variable (1M) & 7514.0 & 7437.4 & 397.2 \\ 3101 Java @notify@ monitor (1M) & 8717.0 & 8774.1 & 471.8 \\ 3102 % Java @notify@ monitor (100 000 000) & 8634.0 & 8683.5 & 330.5 \\ 3103 Pthreads cond. variable (1M) & 5553.7 & 5576.1 & 345.6 3093 \multicolumn{1}{@{}c}{} & \multicolumn{1}{c}{Median} & \multicolumn{1}{c}{Average} & \multicolumn{1}{c@{}}{Std Dev} \\ 3094 \CFA @signal@, 1 monitor & 364.4 & 364.2 & 4.4 \\ 3095 \CFA @signal@, 2 monitor & 484.4 & 483.9 & 8.8 \\ 3096 \CFA @signal@, 4 monitor & 709.1 & 707.7 & 15.0 \\ 3097 \uC @signal@ monitor & 328.3 & 327.4 & 2.4 \\ 3098 Rust cond. variable & 7514.0 & 7437.4 & 397.2 \\ 3099 Java @notify@ monitor & 9623.0 & 9654.6 & 236.2 \\ 3100 Pthreads cond. variable & 5553.7 & 5576.1 & 345.6 3104 3101 \end{tabular} 3105 3102 \end{multicols} … … 3110 3107 External scheduling is measured using a cycle of two threads calling and accepting the call using the @waitfor@ statement. 3111 3108 Figure~\ref{f:schedext} shows the code for \CFA with results in Table~\ref{t:schedext}. 3112 Note, the \CFA incremental cost for bulk acquire isa fixed cost for small numbers of mutex objects.3109 Note, the incremental cost of bulk acquire for \CFA, which is largely a fixed cost for small numbers of mutex objects. 3113 3110 3114 3111 \begin{multicols}{2} 3115 \ setlength{\tabcolsep}{5pt}3112 \lstset{language=CFA,moredelim=**[is][\color{red}]{@}{@},deletedelim=**[is][]{`}{`}} 3116 3113 \vspace*{-16pt} 3117 \begin{cfa} [xleftmargin=0pt]3118 `monitor`M {} m1/*, m2, m3, m4*/;3119 void call( M & `mutex p1/*, p2, p3, p4*/`) {}3120 void wait( M & `mutex p1/*, p2, p3, p4*/`) {3121 for ( N ) { `waitfor( call : p1/*, p2, p3, p4*/ );`}3114 \begin{cfa} 3115 @monitor@ M {} m1/*, m2, m3, m4*/; 3116 void call( M & @mutex p1/*, p2, p3, p4*/@ ) {} 3117 void wait( M & @mutex p1/*, p2, p3, p4*/@ ) { 3118 for ( N ) { @waitfor( call : p1/*, p2, p3, p4*/ );@ } 3122 3119 } 3123 3120 thread T {}; … … 3136 3133 \columnbreak 3137 3134 3138 \vspace*{-1 8pt}3135 \vspace*{-16pt} 3139 3136 \captionof{table}{External-scheduling comparison (nanoseconds)} 3140 3137 \label{t:schedext} 3141 3138 \begin{tabular}{@{}r*{3}{D{.}{.}{3.2}}@{}} 3142 \multicolumn{1}{@{} r}{N\hspace*{10pt}} & \multicolumn{1}{c}{Median} &\multicolumn{1}{c}{Average} & \multicolumn{1}{c@{}}{Std Dev} \\3143 \CFA @waitfor@, 1 monitor (10M)& 367.1 & 365.3 & 5.0 \\3144 \CFA @waitfor@, 2 monitor (10M)& 463.0 & 464.6 & 7.1 \\3145 \CFA @waitfor@, 4 monitor (10M)& 689.6 & 696.2 & 21.5 \\3146 \uC \lstinline[language=uC++]|_Accept| monitor (10M)& 328.2 & 329.1 & 3.4 \\3147 Go \lstinline[language=Golang]|select| channel (10M)& 365.0 & 365.5 & 1.23139 \multicolumn{1}{@{}c}{} & \multicolumn{1}{c}{Median} &\multicolumn{1}{c}{Average} & \multicolumn{1}{c@{}}{Std Dev} \\ 3140 \CFA @waitfor@, 1 monitor & 367.1 & 365.3 & 5.0 \\ 3141 \CFA @waitfor@, 2 monitor & 463.0 & 464.6 & 7.1 \\ 3142 \CFA @waitfor@, 4 monitor & 689.6 & 696.2 & 21.5 \\ 3143 \uC \lstinline[language=uC++]|_Accept| monitor & 328.2 & 329.1 & 3.4 \\ 3144 Go \lstinline[language=Golang]|select| channel & 365.0 & 365.5 & 1.2 3148 3145 \end{tabular} 3149 3146 \end{multicols} … … 3158 3155 3159 3156 \begin{multicols}{2} 3160 \ setlength{\tabcolsep}{3pt}3161 \begin{cfa} [xleftmargin=0pt]3162 `monitor`M {} m1/*, m2, m3, m4*/;3163 call( M & `mutex p1/*, p2, p3, p4*/`) {}3157 \lstset{language=CFA,moredelim=**[is][\color{red}]{@}{@},deletedelim=**[is][]{`}{`}} 3158 \begin{cfa} 3159 @monitor@ M {} m1/*, m2, m3, m4*/; 3160 call( M & @mutex p1/*, p2, p3, p4*/@ ) {} 3164 3161 int main() { 3165 3162 BENCH( for( N ) call( m1/*, m2, m3, m4*/ ); ) … … 3176 3173 \label{t:mutex} 3177 3174 \begin{tabular}{@{}r*{3}{D{.}{.}{3.2}}@{}} 3178 \multicolumn{1}{@{}r}{N\hspace*{10pt}} & \multicolumn{1}{c}{Median} &\multicolumn{1}{c}{Average} & \multicolumn{1}{c@{}}{Std Dev} \\ 3179 test-and-test-set lock (50M) & 19.1 & 18.9 & 0.4 \\ 3180 \CFA @mutex@ function, 1 arg. (50M) & 48.3 & 47.8 & 0.9 \\ 3181 \CFA @mutex@ function, 2 arg. (50M) & 86.7 & 87.6 & 1.9 \\ 3182 \CFA @mutex@ function, 4 arg. (50M) & 173.4 & 169.4 & 5.9 \\ 3183 \uC @monitor@ member rtn. (50M) & 54.8 & 54.8 & 0.1 \\ 3184 Goroutine mutex lock (50M) & 34.0 & 34.0 & 0.0 \\ 3185 Rust mutex lock (50M) & 33.0 & 33.2 & 0.8 \\ 3186 Java synchronized method (50M) & 31.0 & 30.9 & 0.5 \\ 3187 % Java synchronized method (10 000 000 000) & 31.0 & 30.2 & 0.9 \\ 3188 Pthreads mutex Lock (50M) & 31.0 & 31.1 & 0.4 3175 \multicolumn{1}{@{}c}{} & \multicolumn{1}{c}{Median} &\multicolumn{1}{c}{Average} & \multicolumn{1}{c@{}}{Std Dev} \\ 3176 test-and-test-set lock & 19.1 & 18.9 & 0.4 \\ 3177 \CFA @mutex@ function, 1 arg. & 48.3 & 47.8 & 0.9 \\ 3178 \CFA @mutex@ function, 2 arg. & 86.7 & 87.6 & 1.9 \\ 3179 \CFA @mutex@ function, 4 arg. & 173.4 & 169.4 & 5.9 \\ 3180 \uC @monitor@ member rtn. & 54.8 & 54.8 & 0.1 \\ 3181 Goroutine mutex lock & 34.0 & 34.0 & 0.0 \\ 3182 Rust mutex lock & 33.0 & 33.2 & 0.8 \\ 3183 Java synchronized method & 31.0 & 31.0 & 0.0 \\ 3184 Pthreads mutex Lock & 31.0 & 31.1 & 0.4 3189 3185 \end{tabular} 3190 3186 \end{multicols} … … 3205 3201 % To: "Peter A. Buhr" <pabuhr@plg2.cs.uwaterloo.ca> 3206 3202 % Date: Fri, 24 Jan 2020 13:49:18 -0500 3207 % 3203 % 3208 3204 % I can also verify that the previous version, which just tied a bunch of promises together, *does not* go back to the 3209 3205 % event loop at all in the current version of Node. Presumably they're taking advantage of the fact that the ordering of … … 3215 3211 3216 3212 \begin{multicols}{2} 3217 \begin{cfa}[xleftmargin=0pt] 3218 `coroutine` C {}; 3219 void main( C & ) { for () { `suspend;` } } 3213 \lstset{language=CFA,moredelim=**[is][\color{red}]{@}{@},deletedelim=**[is][]{`}{`}} 3214 \begin{cfa}[aboveskip=0pt,belowskip=0pt] 3215 @coroutine@ C {}; 3216 void main( C & ) { for () { @suspend;@ } } 3220 3217 int main() { // coroutine test 3221 3218 C c; 3222 BENCH( for ( N ) { `resume( c );`} )3219 BENCH( for ( N ) { @resume( c );@ } ) 3223 3220 sout | result; 3224 3221 } 3225 3222 int main() { // thread test 3226 BENCH( for ( N ) { `yield();`} )3223 BENCH( for ( N ) { @yield();@ } ) 3227 3224 sout | result; 3228 3225 } … … 3237 3234 \label{t:ctx-switch} 3238 3235 \begin{tabular}{@{}r*{3}{D{.}{.}{3.2}}@{}} 3239 \multicolumn{1}{@{}r}{N\hspace*{10pt}} & \multicolumn{1}{c}{Median} &\multicolumn{1}{c}{Average} & \multicolumn{1}{c@{}}{Std Dev} \\ 3240 C function (10B) & 1.8 & 1.8 & 0.0 \\ 3241 \CFA generator (5B) & 1.8 & 2.0 & 0.3 \\ 3242 \CFA coroutine (100M) & 32.5 & 32.9 & 0.8 \\ 3243 \CFA thread (100M) & 93.8 & 93.6 & 2.2 \\ 3244 \uC coroutine (100M) & 50.3 & 50.3 & 0.2 \\ 3245 \uC thread (100M) & 97.3 & 97.4 & 1.0 \\ 3246 Python generator (100M) & 40.9 & 41.3 & 1.5 \\ 3247 Node.js await (5M) & 1852.2 & 1854.7 & 16.4 \\ 3248 Node.js generator (100M) & 33.3 & 33.4 & 0.3 \\ 3249 Goroutine thread (100M) & 143.0 & 143.3 & 1.1 \\ 3250 Rust async await (100M) & 32.0 & 32.0 & 0.0 \\ 3251 Rust tokio thread (100M) & 143.0 & 143.0 & 1.7 \\ 3252 Rust thread (25M) & 332.0 & 331.4 & 2.4 \\ 3253 Java thread (100M) & 405.0 & 415.0 & 17.6 \\ 3254 % Java thread ( 100 000 000) & 413.0 & 414.2 & 6.2 \\ 3255 % Java thread (5 000 000 000) & 415.0 & 415.2 & 6.1 \\ 3256 Pthreads thread (25M) & 334.3 & 335.2 & 3.9 3236 \multicolumn{1}{@{}c}{} & \multicolumn{1}{c}{Median} &\multicolumn{1}{c}{Average} & \multicolumn{1}{c@{}}{Std Dev} \\ 3237 C function & 1.8 & 1.8 & 0.0 \\ 3238 \CFA generator & 1.8 & 2.0 & 0.3 \\ 3239 \CFA coroutine & 32.5 & 32.9 & 0.8 \\ 3240 \CFA thread & 93.8 & 93.6 & 2.2 \\ 3241 \uC coroutine & 50.3 & 50.3 & 0.2 \\ 3242 \uC thread & 97.3 & 97.4 & 1.0 \\ 3243 Python generator & 40.9 & 41.3 & 1.5 \\ 3244 Node.js await & 1852.2 & 1854.7 & 16.4 \\ 3245 Node.js generator & 33.3 & 33.4 & 0.3 \\ 3246 Goroutine thread & 143.0 & 143.3 & 1.1 \\ 3247 Rust async await & 32.0 & 32.0 & 0.0 \\ 3248 Rust tokio thread & 143.0 & 143.0 & 1.7 \\ 3249 Rust thread & 332.0 & 331.4 & 2.4 \\ 3250 Java thread & 405.0 & 415.0 & 17.6 \\ 3251 Pthreads thread & 334.3 & 335.2 & 3.9 3257 3252 \end{tabular} 3258 3253 \end{multicols} … … 3263 3258 Languages using 1:1 threading based on pthreads can at best meet or exceed, due to language overhead, the pthread results. 3264 3259 Note, pthreads has a fast zero-contention mutex lock checked in user space. 3265 Languages with M:N threading have better performance than 1:1 because there is no operating-system interactions (context-switching or locking). 3266 As well, for locking experiments, M:N threading has less contention if only one kernel thread is used. 3260 Languages with M:N threading have better performance than 1:1 because there is no operating-system interactions. 3267 3261 Languages with stackful coroutines have higher cost than stackless coroutines because of stack allocation and context switching; 3268 3262 however, stackful \uC and \CFA coroutines have approximately the same performance as stackless Python and Node.js generators. 3269 3263 The \CFA stackless generator is approximately 25 times faster for suspend/resume and 200 times faster for creation than stackless Python and Node.js generators. 3270 The Node.js context-switch is costly when asynchronous await must enter the event engine because a promise is not fulfilled.3271 Finally, the benchmark results correlate across programming languages with and without JIT, indicating the JIT has completed any runtime optimizations.3272 3264 3273 3265 … … 3327 3319 3328 3320 The authors recognize the design assistance of Aaron Moss, Rob Schluntz, Andrew Beach, and Michael Brooks; David Dice for commenting and helping with the Java benchmarks; and Gregor Richards for helping with the Node.js benchmarks. 3329 This research is funded by the NSERC/Waterloo-Huawei (\url{http://www.huawei.com}) Joint Innovation Lab. %, and Peter Buhr is partially funded by the Natural Sciences and Engineering Research Council of Canada.3321 This research is funded by a grant from Waterloo-Huawei (\url{http://www.huawei.com}) Joint Innovation Lab. %, and Peter Buhr is partially funded by the Natural Sciences and Engineering Research Council of Canada. 3330 3322 3331 3323 {%
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