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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchThe Hot Code Heap proposal aimed to group selected hot, compiled Java methods more densely inside the JVM’s code cache, potentially improving code locality. That is a proposed benefit, not a demonstrated speedup: the sources available for this topic report no benchmark result for the proposal. Current OpenJDK HotSpot source includes hot-code-heap support, but its exact formal relationship to the 2024 draft is not established here.
What the Hot Code Heap proposal changes
The proposal concerns the JVM’s compiled-code cache, not Java’s object heap. The code cache stores compiled machine code produced by the JIT compiler. In March 2024, a draft proposal described extending the segmented code cache with an optional heap for selected hot methods that are not profiled. Compiler control would let users mark certain methods as hot so they could be compiled into that heap. InfoWorld’s March 25, 2024 report covered the draft, while InfoQ’s March 18, 2024 roundup identified Dmitry Chuyko, BellSoft performance architect, as its proposer.
In practical terms, the design adds an optional destination for methods selected as hot, alongside the existing code-cache organization. It does not mean every method is placed in that heap, nor does it change where ordinary Java objects are allocated.
Why grouping hot methods could help
The proposal’s rationale is locality: if frequently executed compiled methods are packed more densely, executing them may involve less scattered code. InfoWorld reported that the proposal cited potential processor penalties when code is scattered through a large code cache. The effect would depend on how much hot code an application has, how dispersed it is, and the processor involved; the report also noted that large pages may not address the problem on systems where it matters.
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These points explain the motivation, not a universal performance rule. The sources reviewed provide no controlled benchmark or quantified speedup for the proposal. Whether grouping methods helps a particular application would need to be established with workload-specific measurements.
What current OpenJDK source shows
The moving OpenJDK HotSpot codeCache.cpp source, accessed in 2026, includes a HotCodeHeapSize setting and a MethodHot code heap. Its comments label this heap for “Nmethods known to be always hot” and describe allocating it as a code-cache segment when enabled.
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The sizing comments say an application usually has about 20% hot code, described as mostly non-profiled code, and use 20% of the non-profiled heap for the hot heap when its size is calculated automatically. That 20% is an OpenJDK implementation comment and sizing heuristic—not a measured share that applies to every Java application.
This source confirms that hot-heap support exists in the current code. It does not, by itself, verify the support’s formal history, its exact relationship to draft JEP 8328186, or a release assignment.
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How to explore hot-method selection
BellSoft’s hotcode-agent repository describes an adjacent workflow for identifying and directing hot methods. It is a tooling example, not evidence of a general performance gain or proof of the draft’s formal status.
- Use the agent to start a Java Flight Recorder recording and collect execution-profile data.
- Have the tool identify hot methods and generate compiler directives from the profile.
- Apply those directives to the JVM. The repository’s example uses
-XX:+HotCodeHeap. - Inspect code-cache behavior with diagnostics documented by the repository, including
-XX:+PrintCodeCacheand-Xlog:codecache.
To evaluate an application, compare runs under representative workloads and keep the JVM configuration and measurement conditions consistent. The cited repository documents a way to gather and apply directives; it does not report comparative performance results.
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What is known about the proposal’s status
InfoWorld reported on March 25, 2024 that the draft had not been assigned to a specific Java release. Its mention of JDK 23 was a possibility at that time, not confirmation. The available sources do not verify the proposal’s current formal JEP status, release history, or direct implementation history, so the current source code should not be treated as proof of those details.
What Java teams should measure
The proposal’s mechanism suggests questions for a workload-specific evaluation, rather than a performance conclusion:
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- Which methods are actually hot under the application’s representative workload, and how were they identified?
- Does concentrating those methods change code-cache use or fragmentation?
- What are the effects of enabling the separate heap, including any code-cache capacity trade-offs?
- Do application-level latency or throughput measurements improve consistently, and do the results hold across relevant processors and workload phases?
The reviewed sources do not provide comparative measurements for these questions. Without them, the defensible conclusion is that hot-code placement is an intended locality optimization whose benefit must be demonstrated for the workload being evaluated.
