AMD has released detailed insights into Local Data Share (LDS) optimizations for its Instinct MI450 GPUs, focusing on how these improvements enhance performance in GEMM kernels. The company highlights two key challenges: layout mismatches and partition contention, both of which can significantly impact throughput. The optimizations aim to resolve these issues by enabling efficient data movement through the LDS, ultimately improving overall kernel performance.
The first optimization addresses layout mismatches, where operands stored in memory do not match the expected format for matrix operations. This can lead to inefficient data loading and processing. AMD explains that transposed LDS loads, such as the ds_load_tr instruction, can reorganize data on the fly, restoring vectorized access and improving efficiency. This approach reduces the need for multiple small loads, which can strain hardware resources and increase instruction counts.
The second optimization targets partition contention on the physical LDS partitions, where multiple warps accessing the same partition serialize their operations. AMD describes how the compiler’s partition-aware allocator can physically separate data across different partitions, reducing contention and improving throughput. These optimizations are aimed at advanced users who develop GEMM kernels using tools like Gluon and Triton, providing deeper insights into how to structure layouts and avoid performance bottlenecks.
Source: amd
