Exploring Dynamic Compilation and Cross-Layer Object Management Policies for Managed Language Applications

Recent years have witnessed the widespread adoption of managed programming languages that are designed to execute on virtual machines. Virtual machine architectures provide several powerful software engineering advantages over statically compiled binaries, such as portable program representations, additional safety guarantees, automatic memory and thread management, and dynamic program composition, which have largely driven their success. To support and facilitate the use of these features, virtual machines implement a number of services that adaptively manage and optimize application behavior during execution. Such runtime services often require tradeoffs between efficiency and effectiveness, and different policies can have major implications on the system's performance and energy requirements. In this work, we extensively explore policies for the two runtime services that are most important for achieving performance and energy efficiency: dynamic (or Just-In-Time (JIT)) compilation and memory management. First, we examine the properties of single-tier and multi-tier JIT compilation policies in order to find strategies that realize the best program performance for existing and future machines. Our analysis performs hundreds of experiments with different compiler aggressiveness and optimization levels to evaluate the performance impact of varying if and when methods are compiled. We later investigate the issue of how to optimize program regions to maximize performance in JIT compilation environments. For this study, we conduct a thorough analysis of the behavior of optimization phases in our dynamic compiler, and construct a custom experimental framework to determine the performance limits of phase selection during dynamic compilation. Next, we explore innovative memory management strategies to improve energy efficiency in the memory subsystem. We propose and develop a novel cross-layer approach to memory management that integrates information and analysis in the VM with fine-grained management of memory resources in the operating system. Using custom as well as standard benchmark workloads, we perform detailed evaluation that demonstrates the energy-saving potential of our approach. We implement and evaluate all of our studies using the industry-standard Oracle HotSpot Java Virtual Machine to ensure that our conclusions are supported by widely-used, state-of-the-art runtime technology

Communion: a new strategy for memory management in high-performance computer systems

Modern computers present a big gap between peak performance and sustained performance. There are many reasons for this situation, but mainly involving an inefficient usage of computational resources. Nowadays the memory system is the most critical component because of its growing inability to keep up with the processor requests. Technological trends have produced a large and growing gap between CPU speeds and DRAM speeds. Much research has focused this memory system problem, including program optimizing techniques, data locality enhancement, hardware and software prefetching, decoupled architectures, mutithreading, speculative loads and execution. These techniques have got a relative success, but they focus only one component in the hardware or software systems. We present here a new strategy for memory management in high-performance computer systems, named COMMUNION. The basic idea behind this strategy is cooperation. We introduce some interaction possibilities among system programs that are responsible to generate and execute application programs. So, we investigate two specific interactions: between the compiler and the operating system, and among the compiling system components. The experimental results show that it’s possible to get improvements of about 10 times in execution time, and about 5 times in memory demand. In the interaction between compiler and operating system, named Compiler-Aided Page Replacement (CAPR), we achieved a reduction of about 10% in space-time product, with an increase of only 0.5% in the total execution time. All these results show that it’s possible to manage main memory with a better efficiency than current systems.Eje: Procesamiento distribuido y paralelo. Tratamiento de señalesRed de Universidades con Carreras en Informática (RedUNCI

Communion: a new strategy form memory management in high-performance computer

Modern computers present a big gap between peak performance and sustained performance. There are many reasons for this situation, but mainly involving an inefficient usage of computational resources. Nowadays the memory system is the most critical component because of its growing inability to keep up with the processor requests. Technological trends have produced a large and growing gap between CPU speeds and DRAM speeds. Much research has focused this memory system problem, including program optimizing techniques, data locality enhancement, hardware and software prefetching, decoupled architectures, multithreading, speculative loads and execution. These techniques have got a relative success, but they focus only one component in the hardware or software systems. We present here a new strategy for memory management in high-performance computer systems, named COMMUNION. The basic idea behind this strategy is "cooperation". We introduce some interaction possibilities among system programs that are responsible to generate and execute application programs. So, we investigate two specific interactions: between the compiler and the operating system, and among the compiling system components. The experimental results show that it's possible to get improvements of about 10 times in execution time, and about 5 times in memory demand, enhancing the interaction between the compiling system components. In the interaction between compiler and operating system, named Compiler-Aided Page Replacement (CAPR), we achieved a reduction of about 10% in space-time product, with an increase of only 0.5% in the total execution time. All these results show that it s possible to manage main memory with a better efficiency than current systems.Facultad de Informátic

Communion: a new strategy for memory management in high-performance computer systems

Modern computers present a big gap between peak performance and sustained performance. There are many reasons for this situation, but mainly involving an inefficient usage of computational resources. Nowadays the memory system is the most critical component because of its growing inability to keep up with the processor requests. Technological trends have produced a large and growing gap between CPU speeds and DRAM speeds. Much research has focused this memory system problem, including program optimizing techniques, data locality enhancement, hardware and software prefetching, decoupled architectures, mutithreading, speculative loads and execution. These techniques have got a relative success, but they focus only one component in the hardware or software systems. We present here a new strategy for memory management in high-performance computer systems, named COMMUNION. The basic idea behind this strategy is cooperation. We introduce some interaction possibilities among system programs that are responsible to generate and execute application programs. So, we investigate two specific interactions: between the compiler and the operating system, and among the compiling system components. The experimental results show that it’s possible to get improvements of about 10 times in execution time, and about 5 times in memory demand. In the interaction between compiler and operating system, named Compiler-Aided Page Replacement (CAPR), we achieved a reduction of about 10% in space-time product, with an increase of only 0.5% in the total execution time. All these results show that it’s possible to manage main memory with a better efficiency than current systems.Eje: Procesamiento distribuido y paralelo. Tratamiento de señalesRed de Universidades con Carreras en Informática (RedUNCI

Virtual Machine Support for Many-Core Architectures: Decoupling Abstract from Concrete Concurrency Models

The upcoming many-core architectures require software developers to exploit concurrency to utilize available computational power. Today's high-level language virtual machines (VMs), which are a cornerstone of software development, do not provide sufficient abstraction for concurrency concepts. We analyze concrete and abstract concurrency models and identify the challenges they impose for VMs. To provide sufficient concurrency support in VMs, we propose to integrate concurrency operations into VM instruction sets. Since there will always be VMs optimized for special purposes, our goal is to develop a methodology to design instruction sets with concurrency support. Therefore, we also propose a list of trade-offs that have to be investigated to advise the design of such instruction sets. As a first experiment, we implemented one instruction set extension for shared memory and one for non-shared memory concurrency. From our experimental results, we derived a list of requirements for a full-grown experimental environment for further research

PRETZEL: Opening the Black Box of Machine Learning Prediction Serving Systems

Machine Learning models are often composed of pipelines of transformations. While this design allows to efficiently execute single model components at training time, prediction serving has different requirements such as low latency, high throughput and graceful performance degradation under heavy load. Current prediction serving systems consider models as black boxes, whereby prediction-time-specific optimizations are ignored in favor of ease of deployment. In this paper, we present PRETZEL, a prediction serving system introducing a novel white box architecture enabling both end-to-end and multi-model optimizations. Using production-like model pipelines, our experiments show that PRETZEL is able to introduce performance improvements over different dimensions; compared to state-of-the-art approaches PRETZEL is on average able to reduce 99th percentile latency by 5.5x while reducing memory footprint by 25x, and increasing throughput by 4.7x.Comment: 16 pages, 14 figures, 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI), 201