Evaluating the Imagine Stream Architecture

Jung Ho Ahn, William J. Dally, Brucek Khailany, Ujval Kapasi, Abhishek Das
Stanford University
Computer Systems Laboratory

Appears in the Proceedings of the 31st International Symposium on Computer Architecture, Jun. 19-23, 2004, Munich, Germany


This paper describes an experimental evaluation of the prototype Imagine stream processor. Imagine is a stream processor that employs a two-level register hierarchy with 9.7 Kbytes of local register file capacity and 128 Kbytes of stream register file (SRF) capacity to capture producer-consumer locality in stream applications. Parallelism is exploited using an array of 48 floating-point arithmetic units organized as eight SIMD clusters with a 6-wide VLIW per cluster. We evaluate the performance of each aspect of the Imagine architecture using a set of synthetic microbenchmarks, key media processing kernels, and full applications. These micro-benchmarks show that the prototype hardware can attain 7.96 GFLOPS or 25.4 GOPS of arithmetic performance, 12.7 Gbytes/s of SRF bandwidth, 1.58 Gbytes/s of memory system bandwidth, and accept up to 2 million stream processor instructions per second from a host processor. On a set of media processing kernels, Imagine sustained an average of 43% of peak arithmetic performance. An evaluation of full applications provides a breakdown of where execution time is spent. Over full applications, Imagine achieves 39.4% of peak performance, of the remainder on average 36.4% of time is lost due to load imbalance between arithmetic units in the VLIW clusters and limited instruction-level parallelism within kernel inner loops, 10.6% is due to kernel startup and shutdown overhead because of short stream lengths, 7.6% is due to memory stalls, and the rest is due to insufficient host processor bandwidth. Further analysis included in the paper presents the impact of host instruction bandwidth on application performance, particularly on smaller datasets. In summary, the experimental measurements described in this paper demonstrate the high performance and efficiency of stream processing: operating at 200 MHz, Imagine sustains 4.81 GFLOPS on QR decomposition while dissipating 7.42 Watts.


Jung Ho Ahn