Building Efficient and Highly Run-Time Adaptable Virtual Machines
Programming language virtual machines (VMs) realize language semantics, enforce security properties, and execute applications efficiently. Fully Reflective Execution Environments (EEs) are VMs that additionally expose their whole structure and behavior to applications. This enables develop- ers to observe and adapt VMs at run time. However, there is a belief that reflective EEs are not viable for practical usages because such flexibility would incur a high performance overhead.
To refute this belief, we built a reflective EE on top of a highly optimizing dynamic compiler. We introduced a new optimization model that, based on the conjecture that variability of low-level (EE-level) reflective behavior is low in many scenarios, mitigates the most significant sources of the performance overheads related to the reflective capabilities in the EE. Our experiments indicate that reflective EEs can reach peak performance in the order of standard VMs. Concretely, that a) if reflective mechanisms are not used the execution overhead is negligible compared to standard VMs, b) VM operations can be redefined at language-level without incurring in significant overheads, c) for several software adaptation tasks, applying the reflection at the VM level is not only lightweight in terms of engineering effort, but also competitive in terms of performance in comparison to other ad-hoc solutions.
Tue 1 Nov Times are displayed in time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
13:30 - 15:10
|Parallel Virtual Machines with RPython|
|Building Efficient and Highly Run-Time Adaptable Virtual Machines|
Guido ChariUniversity of Buenos Aires, Argentina, Diego GarbervetskyUniversity of Buenos Aires, Argentina, Stefan MarrJohannes Kepler University LinzDOI Pre-print
|Optimizing R Language Execution via Aggressive Speculation|
Lukas StadlerOracle Labs, Austria, Adam WelcOracle Labs, USA, Christian HumerOracle Labs, Switzerland, Mick JordanOracle Labs, USADOI