Views, Programming Language Research, and HPC

8/3/2019 Views, Programming Language Research, and HPC

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Introduction Views Example PL Research Views Technical Details Conclusions

Views, Programming Languages Research,

and HPC

Patrick Lam

http://patricklam.ca

Joint work with Brian Demsky

January 2012

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Context

1.2 5.8 2.2 3.5 8.1

7.

3 9.

1 2.

3 0.

9 2.

28.3 1.1 0.8 3.5 2.9

1.8 3.4 2.8 6.5 9.3

0.8 3.2 3.3 8.2 4.3

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Context

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Roadmap

Views: mutual exclusion via policy-basedlocks

Programming languages and HPC

Technical details on views

D C

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Problem

Current lockingmechanisms are

hard to use.

I t d ti Vi E l PL R h Vi T h i l D t il C l i

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Problems

no guarantee that locks are consistentlyapplied;

no way to express fine-grained locking;

can’t express why locks exist.


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Goal

Raise abstraction level ofconcurrency control

primitives.


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Subgoals

Support object-oriented design principles.

Support fine-grained locking at language level.

Support static checking to help catch

concurrency bugs.


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Array-Based Vector Implementation

2 5 3 1 7 9

sizecapacity

array


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Vector class definition

Vector

size : intcapacity : int

array : int[]

Rule: must hold owning lock to access “size”.


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Basic Approach

Vector

size : int

capacity : intarray : int[]

Declare a view which protects the field.

Must hold the view to access the field—checked by

compiler.

Compiler uses annotations to create efficient lock-based

code.


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p

Concrete Example of Views

1 view read {

2 size, capacity, array: readonly;

3

4 incompatible write, resize;

5

6 get(int i) preferred;

7 capacity();

8 }


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p


1 view read {


3


5


7 capacity();

8 }

Provides read-only access to fields “size”, “capacity” and“array”.


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1 view read {


3


5


7 capacity();

8 }


A thread cannot hold this view on some object while some

other thread holds view “write” or “resize” on that object.


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1 view read {


3


5


7 capacity();

8 }




Methods “get” and “capacity” belong to this view.


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1 view read {


3


5


7 capacity();

8 }




Methods “get” and “capacity” belong to this view.

Calling method “get” will auto-acquire this view.


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Interface of Vector Example

Our Vector provides the following methods:

get()

set()

capacity(): queries current Vector capacity.

resize(): changes Vector capacity, re-copying items.


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Views for Vector Example

capacity: provides read access to capacity field

All other views provide read access to Vectormetadata (size, capacity) and:read: read access to Vector contents (“get”).

write: write access to Vector contents (“set”).

xclRead: read access to Vector contents; only one threadcan hold xclRead.

resize: write access to Vector contents and metadata.


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Resizing the Vector

1 public void resize(int newcapacity) {

2 Object[] newarray = new Object[newcapacity];

3 for(int i=0; i < newcapacity && i < size; i++) {

4 newarray[i] = array[i];

5 }6

7 acquire (this@resize) {

8 array = newarray; capacity = newcapacity;

9 size = (size<newcapacity) ? size : newcapacity;

10 }11 }

1 Copy existing Vector’s contents, holding xclRead view.2 Switch over the Vector to point to the new copy, holding

resize view.


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Views Ensure Mutual Exclusion

Calling resize() auto-acquires xclRead view.

No other thread may write while xclRead view held(xclRead incompatible with write, xclRead, resize).

During the critical switchover phase, no other thread may

access the Vector: all views incompatible with resize view.


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Workflow for using Views

source

code

w/views

view

declarations

compiler

lock

allocation

Java

source

code


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Results

No speedups.

1 Microbenchmarks: views are fast enough.

2 Case studies: views are useful.


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Microbenchmarks

Investigate performance of views, compared to naı̈ve locks and

hand-coded implementations.

Two benchmarks:

Red-black tree

Concurrent hash map

Hardware: dual-processor quad-core Intel Xeon E5520.


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Red-black tree performance

% Writes

T i m e ( m s )

2000

4000

6000

8000

10000

0 5 10 15 20

Java LocksRead-Write LocksViews


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Concurrent hash map performance (vs. % writes)

% Writes

T i m e ( m s )

1000

2000

3000

4000

5000

6000

0 5 10 15 20

java.util.Hashtable (built-in synchronization)ConcurrentHashMap with manual locksConcurrentHashMap with views java.util.concurrent.ConcurrentHashMap


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Concurrent hash map performance (vs. # cores)

Cores

T i m e ( m s )

1000

2000

3000

4000

5000

1 2 4 8

java.util.Hashtable (built-in synchronization)ConcurrentHashMap with manual locksConcurrentHashMap with views java.util.concurrent.ConcurrentHashMap


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Case study results

Implemented Views as a Polyglot (extensible compiler

framework) extension.

Views compiler available for download at

http://demsky.eecs.uci.edu/software.php .

Acquired and ported 4 multi-threaded Java applications:

Vuze file-sharing client

Mailpuccino mail clientTupleSoup database library

jPhoneLite voIP softphone


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Vuze file-sharing client case study

194,000 lines of code total

We modified the buddy plugin for Vuze, 13,500 lines of code

Changed two classes:

BuddyPlugin, 4 views

BuddyTracker, 9 views


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Vuze: BuddyPlugin class

Added 4 views:

read state: provides read access to 11 fields, incompatible

with write statewrite state: provides write access to 11 field, incompatible

with read state and write state

pd queue, publish write contents: lock-like, provide

read/write access to 1 field, incompatible with self

Note how views protect part of the class’s state and ensure

appropriate locks are held.


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Vuze: BuddyPluginTracker class

Most interesting locking structure in buddy plugin.

Converted 5 locks into 6 views:

“this” lock maps to 2 views, “read internal state” and

“write internal state”

other locks generally map to 1 view

For instance:

view “online buddies” provides read/write access to fields

“online buddies”, “online buddy ips”.

view “read internal state” provides read access to 12 fields,

incompatible with “write internal state” and “buddy peers”.


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Mailpuccino graphical mail client

Contains 14,000 lines of code.

Ported the mail folder cache to use views, allowing multiple

threads to simultaneously read the message cache.

Created 4 views in all: 2 sets of 2 views each.

1 lookup and modify views: protect the “KeyValues” field

(which stores the cache) and its accessor methods.

2

file and indexfile views: protect the cache file and its index.Only one

Only one thread may access a file at a time.

Compiler synthesizes 3 locks: 2 normal plus 1 read/write lock.


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Mailpuccino graphical mail client: bad code

Benchmark also contains a class MonitoredInputStream.

Tried to replace two synchronized methods with views.Compiler warned that a third unsynchronized method

accessed a view protected method.

Discovery: MonitorInputStream was not thread safe and

the synchronized methods were never actually called


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jPhoneLite VoIP softphone


Annotated the RTP and RTPChannel classes.

readSamples, writeSamples: protect a circular buffer

containing incoming data.

readSamples writes to the buffer metadata.

readHostPort, writeHostPort: protect destination

information (remoteip, remoteport fields)

Compiler produces 1 read-write lock (host port) and 1 normallock (samples) for RTP, plus 1 normal lock for RTPChannel.

Also kept the original lock on RTP to protect remaining state.


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TupleSoup database library


Three index classes: MemoryIndex, PageIndex, FlatIndex.

Original implementation used one lock to protect all indexes.

Created 2 views per index class: access and modifying.

multiple threads may hold an access view;

only one thread may hold modifying view, and no other

thread may access or modify concurrently.

Compiler uses read-write locks to implement these views.

Also converted a cached table (5 locks) to use views.

one lock was unnecessary; views made this obvious.


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Goals of PL Research

Make programs go faster

(“program optimization”).

Make programs less buggy.

Make developers more productive.


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Optimizing Compilers

Two basic ideas:

1 eliminate redundant work or

unnecessary waiting

2 enable automatic or guided parallelization


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How Compilers Optimize

Static analysis: estimate program behaviour

ahead-of-time.Dynamic analysis: observe program

behaviour on actual inputs.

In either case, the compiler rewrites the programto make it faster.


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Static Analysis Examples

Views implement some static analyses, including:

one to ensure that views held at field accesses;

one to ensure that array references don’t escape.

Example of a standard static analysis for optimization:

1 a = x * y + 3 ;

2 b = c - x * y;⇒

1 t = x * y;

2 a = t + 3;

3 b = c - t;

Common subexpression elimination finds that x * y is evaluated

needlessly.


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Static Analysis for Parallelization

Establishing the absence of cycles enables parallelization oftree operations.

Can use a second-order logic formula to summarize the

reachable heap objects.


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Dynamic Analysis Example: Specialization

1 f(3);

2 f(5);

3 f(3);

4 f(3);

5 f(3);

If the run-time system observes that f is always

called with parameter 3, it can create a

specialized, faster version of f.


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Establishing Program Correctness

Goal: verify that the program meets some specifications.

Implicit: programs are never supposed to dereferencenull pointers;

Lightweight: selected domain-specificproperties/invariants, e.g. conservation of energy;

Full: program does exactly what it is supposed to.


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Techniques for Program Verification

Ad-hoc techniques specialized for a

particular abstraction;

Exhaustive search using model checking;

Automatic theorem proving.


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Improving Programmer Productivity: Beyond

Libraries

Language extensions

Domain-specific languages

Program synthesis


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Language Extensions

Views are one example of a language

extension. Some others:

Type systems: e.g. augmenting types with

units (inches, cm);

Tracematches: specify safety properties

using finite-state machines.


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Domain-Specific Languages

MATLABCan also define e.g. DSLs for numerical

kernels.


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Program Synthesis

Idea: specify some description of the program

without all of the implementation details.

One example: program sketching.

Provide the structure of the implementation;

Provide sample inputs and outputs.

Compiler then synthesizes correct code meeting

the requirements.


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Views: Behind the scenes

source

code

w/views

view

declarations

compiler

lock

allocation

Java

source

code


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Compiler Checks

read/write hazards (on view declarations)

assignment checks

method call checks

inheritance checks


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Lock Synthesis

Compile incompatibility graphs into locks

Locks implement edges in graph

Write lock implements conflict edges in a clique in which allvertices have self edges

Read-write lock implements conflict edges in a clique in

which all vertices but one have self edges

Lock synthesis problem is simply minimum clique coveringUse greedy algorithm


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Related Work: Views

Type systems to ensure absence of data races (Boyapati

et al; Abadi et al; Bacon et al)Race detection tools (Eraser; Choi et al; Marino et al;

RacerX; Warlock; Sema)

Automatic generation of locking schemes for critical

regions (Halpert et al; Emmi et al; Hicks et al; Zhang et al)


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Conclusion

Presented the views concurrency control mechanism:

raise the abstraction level of concurrency control

enable static checking that can help catch concurrency

bugs

Experience indicates that views are:

simple to program with;

support sophisticated fine-grained access control; and

can detect concurrency bugs

Also presented some thoughts about programming languages

and HPC.

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Views, Programming Language Research, and HPC

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