PLDI 2024
Mon 24 - Fri 28 June 2024 Copenhagen, Denmark

This program is tentative and subject to change.

Thu 27 Jun 2024 11:40 - 12:00 at Iceland / Denmark - Managed Languages

The runtimes of managed object-oriented languages such as Java allocate objects on the heap, and rely on automatic garbage collection (GC) techniques for freeing up unused objects. Most such runtimes also consist of just-in-time (JIT) compilers that optimize memory access and GC times by employing escape analysis: an object that does not escape (outlive) its allocating method can be allocated on (and freed up with) the stack frame of the corresponding method. However, in order to minimize the time spent in JIT compilation, the scope of such useful analyses is quite limited, thereby restricting their precision significantly. On the contrary, even though it is feasible to perform precise program analyses statically, it is not possible to use their results in a managed runtime without a closed-world assumption. In this paper, we propose a static+dynamic scheme that allows one to harness the results of a precise static escape analysis for allocating objects on stack, while taking care of both soundness and efficiency concerns in the runtime.

Our scheme comprises of three key ideas. First, using the results of a statically performed escape analysis, it performs optimistic stack allocation during JIT compilation. Second, it handles the challenges associated with features that may invalidate the optimism, using a novel idea of dynamic heapification. Third, it uses another novel notion of stack ordering, again supported by a static analysis, to reduce the overheads associated with the checks that determine the need for heapification. The static and the runtime components of our approach are implemented in the Soot optimization framework and in the tiered infrastructure of the Eclipse OpenJ9 VM, respectively. To evaluate the benefits, we compare our scheme with the existing escape analysis and find that it succeeds in allocating a much larger number of objects on the stack. Furthermore, the enhanced stack allocation leads to a significant reduction in the number of GC cycles and brings decent performance improvements, especially suited for constrained-memory environments.

This program is tentative and subject to change.

Thu 27 Jun

Displayed time zone: Windhoek change

10:40 - 12:20
10:40
20m
Talk
Linear Matching of JavaScript Regular Expressions
PLDI Research Papers
DOI Pre-print
11:00
20m
Talk
RichWasm: Bringing Safe, Fine-Grained, Shared-Memory Interoperability Down to WebAssembly
PLDI Research Papers
Michael Fitzgibbons Northeastern University, Zoe Paraskevopoulou Ethereum Foundation, Noble Mushtak Northeastern University, Michelle Thalakottur Northeastern University, Jose Sulaiman Manzur Northeastern University, Amal Ahmed Northeastern University, USA
DOI
11:20
20m
Talk
Bringing the WebAssembly Standard up to Speed with SpecTec
PLDI Research Papers
Dongjun Youn KAIST, Shin Wonho KAIST, Jaehyun Lee KAIST, Sukyoung Ryu KAIST, Joachim Breitner unaffiliated, Philippa Gardner Imperial College London, Sam Lindley University of Edinburgh, Matija Pretnar University of Ljubljana, Xiaojia Rao Imperial College, Conrad Watt Nanyang Technological University, Andreas Rossberg Independent
DOI
11:40
20m
Talk
Optimistic Stack Allocation and Dynamic Heapification for Managed Runtimes
PLDI Research Papers
Aditya Anand Indian Institute of Technology Bombay, Solai Adithya IIT Mandi, Swapnil Rustagi IIT Mandi, Priyam Seth IIT Mandi, Vijay Sundaresan IBM Canada, Daryl Maier IBM Canada, V Krishna Nandivada IIT Madras, Manas Thakur Indian Institute of Technology Bombay
DOI Pre-print
12:00
20m
Talk
Concurrent Immediate Reference Counting
PLDI Research Papers
Jaehwang Jung KAIST, Jeonghyeon Kim KAIST, Matthew J. Parkinson Microsoft Azure Research, Jeehoon Kang KAIST
DOI