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Scaling Up Performance of Managed Applications on NUMA Systems

Scaling up the performance of managed applications on Non-Uniform Memory Access (NUMA) architectures has been a challenging task, as it requires a good understanding of the …

TeraHeap: Reducing Memory Pressure in Managed Big Data Frameworks

Big data analytics frameworks, such as Spark and Giraph, need to process and cache massive amounts of data that do not always fit on the managed heap. Therefore, frameworks …

A Multifaceted Memory Analysis of Java Benchmarks

Java benchmarking suites like Dacapo and Renaissance are employed by the research community to evaluate the performance of novel features in managed runtime systems. These suites …

You Can’t Hide You Can’t Run: A Performance Assessment of Managed Applications on a NUMA Machine

Say Goodbye to Off-heap Caches! On-heap Caches Using Memory-Mapped I/O

Efficient Compilation and Execution of JVM-Based Data Processing Frameworks on Heterogeneous Co-Processors

An Analysis of Call-Site Patching without Strong Hardware Support for Self-Modifying-Code

Dynamic Application Reconfiguration on Heterogeneous Hardware

By utilizing diverse heterogeneous hardware resources, developers can significantly improve the performance of their applications. Currently, in order to determine which parts of …

On the future of research VMs: a hardware/software perspective

Exploiting High-performance Heterogeneous Hardware for Java Programs Using Graal