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  1. Proceedings of the 2017 ACM SIGPLAN International Symposium on Memory Management (ISMM 2017)
  2. Flexible and efficient memory object metadata
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Bridging the gap between memory performance and massive parallelism: the critical role of programming systems innovations (keynote)
NG2C: pretenuring garbage collection with dynamic generations for HotSpot big data applications
A marshalled data format for pointers in relocatable data blocks
Analyzing memory management methods on integrated CPU-GPU systems
"What's in a name?" going beyond allocation site names in heap analysis
Type-assisted automatic garbage collection for lock-free data structures
Flexible and efficient memory object metadata
Continuous checkpointing of HTM transactions in NVM
A refinement hierarchy for free list memory allocators
Shadow state encoding for efficient monitoring of block-level properties
RTHMS: a tool for data placement on hybrid memory system
Avoiding consistency exceptions under strong memory models

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Flexible and efficient memory object metadata

Content Provider ACM Digital Library
Author Criswell, John Liu, Zhengyang
Abstract Compiler-based tools can protect software from attack and find bugs within programs. To support programs written in type-unsafe languages such as C, such tools need to add code into a program that must, at run-time, take a pointer into a memory object and locate metadata for that memory object. Current methods of locating metadata are either flexible (supporting metadata of varying sizes) at the expense of speed and scalability or are fast (e.g., by using shadow tables) at the cost of flexibility (metadata is small and must always be the same size). This paper presents a new method of attaching metadata to memory objects, named Padding Area MetaData (PAMD), that is both flexible and efficient. Metadata can be any size, and different memory objects can have different sized metadata. While flexible, the algorithm for finding the metadata given a pointer into the memory object takes constant time. Our method extends Baggy Bounds with Accurate Checking (BBAC) which attaches constant-sized metadata to memory objects for performing precise dynamic bounds checks. Our design supports variable-sized metadata, and our implementation supports larger programs. We evaluated the performance and scalability of PAMD using dynamic bounds checking as an exemplar of our method. Our results show that our method adds at most 33% overhead to an identical dynamic bounds checking tool that trades precision for performance by using a simple shadow table. Our results also show that our method, while having the same flexibility as splay trees, performs significantly faster and scales better as a program allocates more memory. .
Starting Page 36
Ending Page 46
Page Count 11
File Format PDF
ISBN 9781450350440
DOI 10.1145/3092255.3092268
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2017-06-18
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Dynamic analysis Memory metadata Memory safety Security hardening Shadow table
Content Type Text
Resource Type Article
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