China’s Coal Chemical Industry: In the View of Governance Challenges

This paper examines the China’s coal chemical strategy. As a part of national energy strategy, China’s coal chemical industry induces conflicts on technical level, economic level and policy level. The analysis of this paper is under the policy framework and discusses the causes and effects of these conflicts and also proposes some possible solutions

China’s Coal Chemical Industry: In the View of Governance Challenges

This paper examines the China’s coal chemical strategy. As a part of national energy strategy, China’s coal chemical industry induces conflicts on technical level, economic level and policy level. The analysis of this paper is under the policy framework and discusses the causes and effects of these conflicts and also proposes some possible solutions

ShareJIT: JIT Code Cache Sharing across Processes and Its Practical Implementation

Just-in-time (JIT) compilation coupled with code caching are widely used to improve performance in dynamic programming language implementations. These code caches, along with the associated profiling data for the hot code, however, consume significant amounts of memory. Furthermore, they incur extra JIT compilation time for their creation. On Android, the current standard JIT compiler and its code caches are not shared among processes---that is, the runtime system maintains a private code cache, and its associated data, for each runtime process. However, applications running on the same platform tend to share multiple libraries in common. Sharing cached code across multiple applications and multiple processes can lead to a reduction in memory use. It can directly reduce compile time. It can also reduce the cumulative amount of time spent interpreting code. All three of these effects can improve actual runtime performance. In this paper, we describe ShareJIT, a global code cache for JITs that can share code across multiple applications and multiple processes. We implemented ShareJIT in the context of the Android Runtime (ART), a widely used, state-of-the-art system. To increase sharing, our implementation constrains the amount of context that the JIT compiler can use to optimize the code. This exposes a fundamental tradeoff: increased specialization to a single process' context decreases the extent to which the compiled code can be shared. In ShareJIT, we limit some optimization to increase shareability. To evaluate the ShareJIT, we tested 8 popular Android apps in a total of 30 experiments. ShareJIT improved overall performance by 9% on average, while decreasing memory consumption by 16% on average and JIT compilation time by 37% on average.Comment: OOPSLA 201