1. Implementing Chares in a High-Level Scripting Language
LuaCharm:
Implementing Chares in a
High-Level Scripting Language
Thiago Ponte, Noemi Rodriguez
PUC-Rio – Brazil

2. If you optimize everything, you will always be unhappy.
Don Knuth

3. Outline
Introduction
Objectives
Lua
LuaCharm
Tests
Summary
Future Work

4. Introduction
Scripting languages have been drawing much attention over the past years
Dynamism, flexibility and simplicity are the main focus of scripting languages
Parallel computing has not yet explored the potential of scripting

5. Objectives Integrate Charm++ and Lua in way that:
Chares can be implemented in Lua
Chares implemented in Lua are perceived as regular C++ chares
Chares can have their implementation changed at runtime
Allow flow of control to be writen in a high level language

6. Lua
Developed at PUC-Rio
Has become an important language

7. Lua

8. Lua fast, lightweight, powerful, embeddable scripting language
dynamic typing; types are associated to values, not variables
all values are first class
single data-structuring facility
tables implement associative arrays
metadata mechanisms allow semantics to be extended

9. Lua
Lua offers a object-oriented like syntax, in which objects are implemented as tables
Previous experience in integrating Lua with other systems such as Corba and COM and languages, such as Java and .NET
myObj = { …
foo = function(self, …)
-- lua code
end, }
myObj:foo(…)
myObj = {}
function myObj:foo(…)
-- lua code
end
myObj:foo(…)

10. LuaCharm
LuaCharm is an extension of Charm++ through changes in parser and code generator
Developed after studying existing binding between Lua and Python
LuaCharm offers a mechanism to implement chares in Lua
The parser generates a façade C++ class responsible for the execution of the corresponding method in Lua

11. LuaCharm Changes in the interface file and code generator:
Inclusion of the attribute lua to be used in chares, followed by the name of the file implementing the chare
Besides the methods declared in the interface file, an updateChare method is created, and it may be used to execute a chunk of lua code inside the chare

12. LuaCharm
Exports a library to Lua that allows instantiation of chares in a simples Lua-like manner
Chares returned to Lua can be called with the “object-oriented” syntax of Lua

13. LuaCharm – Chare definition
chare [lua "luaChare.lua"] luaChare{
entry luaChare();
entry someLuaMethod(); }
luaChare = {
ckNew = function()
-- lua code
end,
someLuaMethod = function()
end
-- chare instantiation
c = charm.luaChare()
-- calling a remote method
c.someLuaMethod()

14. Integrating with Load Balancing
Chares implemented in Lua can be migrated by the load balancer.
The Lua implementation must implement a pack and a unpack method to migrate values. pack must return a string, which unpack will receive as parameter

15. Tests Adaptive Quadrature of the ex function between 0 and 15
Implementations using bag of tasks and division in fixed intervals
Four different approaches:
Standard Charm++ implementation
Controller in Lua and workers in C++
Both chares in Lua
Both chares in Lua, but the workers using a library implemented in C for the mathematical calculations

16. Tests – Bag of Tasks Bag of tasks sends an interval to a worker N;
Worker checks if interval should be broken down;
If yes, sends back part of the interval;
Calculates the result for its interval;
Send back the result.

17. Tests
First approach using bag of tasks in the mainchare and a chare group for workers.
Tested in 8 processors
1 Impl
2 Impl
3 Impl
4 Impl
Time(s)
29.75
29.85
168.77
30.59
Increase in relation to 1
0.35%
467.36%
2.82%

18. Tests
Second approach, using an array of 500 chares, where each is responsible for a pre-determined part of the problem.
Tested in 8 processors
1ª Impl
2ª Impl
3ª Impl
4ª Impl
Time(s)
10.01
67.83
Increase in relation to 1 0%
577.66%
0.03%

19. Summary
Even when the chares were all implemented in Lua, but with a C library for the mathematical work, the increase in processing time was acceptable
Since Lua chares are regular chares, profiling results are easy to read

20. Future Work Optimizations in the generated code
Experiments with runtime redefinitions
application strategy
load balancer
Restrictions in the implementation:
Read-only variables
Array reductions
Using Messages
Synchronous non-blocking remote calls using coroutines

21. Thank You Questions? More details? Coming soon…  ?