An Efficient Compilation Framework for Languages Based on a Concurrent Process Calculus

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An Efficient Compilation Frameworkfor Languages
Based on a Concurrent Process Calculus

• Yoshihiro Oyama Kenjiro Taura Akinori
  Yonezawa
• Yonezawa Laboratory
• Department of Information Science
• University of Tokyo

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Compiling Programming Languages
implementation is difficult analysis is not
general
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Intermediate Languages

• Sequential languages
• Quadruple
• Lambda calculus
• Continuation Passing Style (CPS) Appel 92
• Concurrent languages
• Pi-calculus Milner 93
• HACL Kobayashi et al. 94

process calculus
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Concurrent Process Calculus

• Key component of calculation
• Asynchronous process
• Communication channel
• Advantages
• Clear syntax and clear semantics
• Many theoretical results for optimization

P
3
P
P
C
3
P
P
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Goal

• Efficient implementation of a process calculus

Schematic code
HACL code
ML-like code
..
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Motivation

• Process calculus has some overheads which are not
• in sequential languages
• Dynamic process scheduling
• Channel communication

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Contribution

• A framework for compiling process calculus
  efficiently
• Optimization techniques applicable for software
  multithreading

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Overview of This Presentation

• Target language HACL
• A basic execution
• Our enhanced execution
• To reduce scheduling overhead
• To reduce communication overhead
• Experimental results

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Target Language HACL
process definition
x0 (x1, , xn) P
process expression
parallel execution
P
P1 P2
channel creation
x. P
receive from e
e(x)gtP
send e2 to e1
e1 lt e2
process instantiation
e0 (e1, , en)
if e then P1 else P2
conditional
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Basic Execution Model (1/2)- process scheduling -
P1 P2 dynamic process creation
schedulable process

P2
P1
P
P2
P
P
scheduling pool
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Basic Execution Model (2/2)- channel -
channel ? pointer to memory space
r
value queue
r(x)gtP
r(y)gtQ
rlt12
rlt8
12
Q
rlt12
process queue
12 / x P
r(x)gtP
r(y)gtQ
8 / y Q
rlt8
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Inefficiencies of Basic Model

• Scheduling overhead
• Scheduling pool is manipulated every time
  a process is created
• Communication overhead
• Channel communication is always performed through
  memory

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Our Enhanced Execution Model

• Static process scheduling
• reduces the frequency of the runtime scheduling
  pool manipulation
• lines up code fragments for multiple process
  expressions
• Unboxed channel framework
• enables us to communicate values without memory
• initially creates a channel on register
• later allocates a channel on heap as necessary

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Compilation Overview
execution flow scheduling pool
implicit
HACL program
translation rule
a set of schedulable process expressions
F P1, P2, ..., Pn a sequential ML-like
program which schedules P1, P2, ..., Pn
execution flow scheduling pool
ML-like program
explicit
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Compilation with Static Scheduling (1/2)
code fragment for P3

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Compilation with Static Scheduling (2/2)
code fragment for P2

code fragment for P2
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Compilation Example
r.(r lt 5 r(x)gt P)
F (r.(r lt 5 r(x)gt P))
r new_channel()
if (r has a waiting process) then ( wake
up the process and ) else put_value(r, 5)
F (r lt 5 r(x)gt P)
F (r lt 5) , (r(x)gt P)
F r(x)gt P
if (r has a value) then x get_value(r)
F P else ( allocate a closure P in
heap and ... ) F
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Unboxed Channel Scheme

• Unboxed channel channel allocated on register
• No memory access to manipulate an unboxed channel
• All channels are created as an unboxed channel
• An unboxed channel is elevated to a
  heap-allocated one as necessary

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Example
r EMPTY_CHANNEL if (...) ... else r
5 VAL_TAG if (...) x r - VAL_TAG
... else ... ...
r new_channel() if (r has a process) then
... else put_value(r, 5) if (r has a
value) then x get_value(r) F
P else ...
ML-like code
Corresponding C code
Channel allocation and communication on a register
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When to allocate a space on heap?
two values are sent
an unboxed channel is duplicated
???
P1
P2
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Experimental Results (1/2)

• HACL is used as an intermediate language of
  Schematic Taura et al. 96
• ML-like program is compiled to assembly-like C
• A native code is generated by GNU C compiler
• Runtime type checks are omitted
• SS20 (HyperSparc 150MHz)
• Now implementing on a large-scale SMP

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Experimental Results (2/2)
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Related Work (1/2)

• Id Schauser et al. 95, Fleng Araki et al. 97
• Static scheduling ? sequentialization
• A does not depend on B ? A B ? A B
• Pict Turner 96
• All channel communications need memory operation
• A receive (input) expression always allocate a
  closure whether a value is present or not

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Related Work (2/2)

• StackThreads Taura et al. 94, 97
• An original proposal of unboxed channel
• Linear channel Kobayashi et al. 96, Igarashi 97
• Linear channel channel used only once
• Some communications for linear channel is
  statically eliminated
• CPS Appel 92
• A compilation framework for sequential language

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Conclusion

• We proposed a framework compiling process
  calculus efficiently
• Static scheduling
• Unboxed channel
• A language based on a process calculus is
  executed only a few times slower than C

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Surface Languages for Process Calculi
surface language
intermediate language
machine code
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A Schedulable Closure and The Scheduling Stack
F f(r, x), P
f(r, x)
P