In recent years,in order to exploit the performance advantage of persistent memory, researchers have designed various lightweight persistent transactional memory systems. Atomicity and consistency of transactions are mostly ensuredusing the logging mechanism. However,compared with conventional memory,memory cells of persistent memory tend to have higher write latency and limited endurance. This paper observes two problems in the existing persistent transactional memory systems: Firstly,existing systems do not distinguish between different types of write operations in the transaction. No matter whether the writes are updating existing data in memory or adding data to newly allocated memory, existing systems use the same logging mechanism to ensure consistency. Secondly,existing systems persist the address and data of every write operation to the log, even if most of them can be compressed to reduce the size. Both of the above problems lead to redundant log operations,resulting in extra write latency and write wearing. In order to solve the above problems,this paper designs and implements TLPTM,a tiny-log persistent transactional memory system. It is based on two optimization techniques: (1)AALO (allocation-aware log optimization), effectively avoids the logging overhead generated by the operations of adding data to newly allocated memory; (2)CBLO (compression-based log optimization), compresses the log before writing it to the NVM and reduces the overhead of logwriting. The experimental results show that compared with Mnemosyne, AALO improves the system performance by 15%~24%, and TLPTM using both optimizations reduces the write wearing of logging by 70%~81%.