Memory management

About: Memory management is a research topic. Over the lifetime, 16743 publications have been published within this topic receiving 312028 citations. The topic is also known as: memory allocation.

Vmalloc: A General and Efficient Memory Allocator

Abstract: Despite its popularity, malloc's shortcomings frequently cause programmers to code around it. The new library Vmalloc generalizes malloc to give programmers more control over memory allocation. Vmalloc introduces the idea of organizing memory into separate regions, each with a discipline to get raw memory and a method to manage allocation. Applications can write their own disciplines to manipulate arbitrary type of memory or just to better organize memory in a region by creating new regions out of its memory. The provided set of allocation methods include general purpose allocation, fast special cases and aids for memory debugging or profiling. A compatible malloc interface enables current applications to select allocation methods using environment variables so they can tune for performance or perform other tasks such as profiling memory usage, generating traces of allocation calls or debugging memory errors. A performance study comparing Vmalloc and currently popular malloc implementations shows that Vmalloc is competitive to the best of these allocators. Applications can gain further performance improvement by using the right mixture of regions with different Vmalloc methods.

GPU-Aware MPI on RDMA-Enabled Clusters: Design, Implementation and Evaluation

Abstract: Designing high-performance and scalable applications on GPU clusters requires tackling several challenges. The key challenge is the separate host memory and device memory, which requires programmers to use multiple programming models, such as CUDA and MPI, to operate on data in different memory spaces. This challenge becomes more difficult to tackle when non-contiguous data in multidimensional structures is used by real-world applications. These challenges limit the programming productivity and the application performance. We propose the GPU-Aware MPI to support data communication from GPU to GPU using standard MPI. It unifies the separate memory spaces, and avoids explicit CPU-GPU data movement and CPU/GPU buffer management. It supports all MPI datatypes on device memory with two algorithms: a GPU datatype vectorization algorithm and a vector based GPU kernel data pack and unpack algorithm. A pipeline is designed to overlap the non-contiguous data packing and unpacking on GPUs, the data movement on the PCIe, and the RDMA data transfer on the network. We incorporate our design with the open-source MPI library MVAPICH2 and optimize a production application: the multiphase 3D LBM. Besides the increase of programming productivity, we observe up to 19.9 percent improvement in application-level performance on 64 GPUs of the Oakley supercomputer.

An Implementation of Scoped Memory for Real-Time Java

Abstract: This paper presents our experience implementing the memory management extensions in the Real-Time Specification for Java. These extensions are designed to given real-time programmers the control they need to obtain predictable memory system behavior while preserving Java's safe memory model.We describe our implementation of certain dynamic checks required by the Real-Time Java extensions. In particular, we describe how to perform these checks in a way that avoids harmful interactions between the garbage collector and the memory management system. We also found that extensive debugging support was necessary during the development of Real-Time Java programs. We therefore used a static analysis and a dynamic debugging package during the development of our benchmark applications.

Multiprocessor system with each processor executing the same instruction sequence and hierarchical memory providing on demand page swapping

Abstract: A computer system employs multiple CPUs, all executing the same instruction stream, with multiple, identical memory modules storing duplicates of the same data and accessable by all the CPUs, providing global memory. The multiple CPUs are loosely synchronized, as by detecting events such as memory references and stalling any CPU ahead of others until all execute the function simultaneously. Each CPU has its own fast cache and also a local memory not accessable by the other CPUs. A hierarchical virtual memory management arrangement for this system employs demand paging to keep the most-used data in the local memory, page-swapping with the global memory. Page swapping with disk memory is through the global memory; the global memory is used as a disk buffer and also to hold pages likely to be needed for loading to local memory. The operating system kernal is kept in local memory. This arrangement is particularly useful in fault-tolerant computer systems.

Methods and systems for achieving high assurance computing using low assurance operating systems and processes

Abstract: A computing system contains and uses a partitioning microkernel (PMK) or equivalent means for imposing memory partitioning and isolation prior to exposing data to a target operating system or process, and conducts continuing memory management whereby data is validated by security checks before or between sequential processing steps. The PMK may be used in conjunction with an Object Request Broker.