HotSpot (virtual machine) | EPFL Graph Search

HotSpot, released as Java HotSpot Performance Engine, is a Java virtual machine for desktop and server computers, developed by Sun Microsystems and now maintained and distributed by Oracle Corporation. It features improved performance via methods such as just-in-time compilation and adaptive optimization. History The Java HotSpot Performance Engine was released on April 27, 1999, built on technologies from an implementation of the programming language Smalltalk named Strongtalk, originally developed by Longview Technologies, which traded as Animorphic. The Longview virtual machine was based on the Self virtual machine, with an interpreter replacing the fast-and-dumb first compiler. When Sun cancelled the Self project, two key people, Urs Hölzle and Lars Bak left Sun to start Longview. In 1997, Sun Microsystems purchased Animorphic. Shortly after acquiring Animorphic, Sun decided to write a new just-in-time (JIT) compiler for

Interflow: interprocedural flow-sensitive type inference and method duplication

Martin Odersky, Denys Shabalin

Scala heavily relies on a number of object-oriented abstractions to support its feature-rich collections library. There are known techniques that optimize those abstractions away in just-in-time (JIT) compilers, but applying them in the ahead-of-time (AOT) setting is problematic. Profile-guided optimization (PGO) lets AOT compilers apply some of the same optimizations that JIT compilers employ, but it comes at a high complexity cost. In this paper, we introduce Interflow, an alternative approach towards ahead-of-time optimization of Scala programs which relies on interprocedural flow-sensitive type inference and method duplication. Our evaluation shows that an Interflow-based optimizing compiler built on top of the Scala Native toolchain outperforms existing PGO-based optimizing compilers for Scala. Moreover, we demonstrate that Interflow and PGO can be combined to achieve further improvements. On our benchmarks, with both Interflow and PGO enabled, the Scala Native toolchain approaches the performance of the HotSpot JVM.

2018

Just-in-time performance without warm-up

Denys Shabalin

Scala has been developed as a language that deeply integrates with the Java ecosystem. It offers seamless interoperability with existing Java libraries. Since the Scala compiler targets Java bytecode, Scala programs have access to high-performance runtimes including the HotSpot virtual machine. HotSpot provides impressive performance results achieved via just-in-time compilation. It starts program execution in interpreter mode, collecting profile feedback about called methods. This information allows HotSpot to identify hot spots in the program, which are then compiled on the fly to native code. This compilation scheme enables high peak performance at the cost of warmup time required to collect the profile data and perform just-in-time compilation. This is a good example of the traditional tradeoff between ahead-of-time (AOT) and just-in-time (JIT) compilation. With AOT, compilers have less information, but the runtime story is reasonably straightforward. With JIT, compilers have more information, which enables advanced optimizations, but the runtime story becomes complicated. In this dissertation, we present the design and implementation of Scala Native, an optimizing compiler for Scala. With Scala Native, Scala programs are compiled ahead of time, which avoids runtime compilation and enables instant startup times. On the other hand, Scala Native is able to match and supersede the peak performance of HotSpot on our benchmarks. In addition to that, Scala Native is a general-purpose Scala compiler - programs compiled by Scala Native closely match the behavior of programs compiled by the Scala compiler. First, we introduce NIR, an intermediate representation designed with ahead-of-time compilation in mind. NIR represents programs in the single-static assignment form and has support for object-oriented features such as virtual dispatch and multiple inheritance. This representation is a key enabler of our compilation and optimization pipeline. Secondly, we present Interflow, a link-time optimizer that takes advantage of the closed-world assumption to optimize the whole program at once. Our optimizer employs a number of techniques including partial evaluation, allocation sinking, and method duplication. The combination of these techniques allows Scala Native to outperform HotSpot on the majority of our benchmarks. Finally, we describe how to improve runtime performance even further based on profile feedback. We propose a technique that splits methods apart isolating key hot paths that are then optimized more aggressively than the cold parts of the program. This provides a further performance advantage over HotSpot.

EPFL2020

Managing Heterogeneous Wireless Environments via Hotspot Servers

Giovanni De Micheli

Wireless communication today supports heterogeneous wireless devices with a number of different wireless network interfaces (WNICs). A large fraction of communication is infrastructure based, so the wireless access points and hotspot servers have become more ubiquitous. Battery lifetime is still a critical issue, with WNICs typically consuming a large fraction of the overall power budget in a mobile device. In this work we present a new technique for managing power consumption and QoS in diverse wireless environments using Hotspot servers. We introduce a resource manager module at both Hotspot server and the client. Resource manager schedules communication bursts between it and each client. The schedulers decide what WNIC to employ for communication, when to communicate data and how to minimize power dissipation while maintaining an acceptable QoS based on the application needs. We present two new scheduling policies derived from well known earliest deadline first (EDF) and rate monotonic (RM) [26] algorithms. The resource manager and the schedulers have been implemented in the HP’s Hotspot server [14]. Our measurement and simulation results show a significant improvement in power dissipation and QoS of Bluetooth and 802.11b for applications such as MP3, MPEG4, WWW, and email.

2005

Just-in-time performance without warm-up

Denys Shabalin

EPFL2020