1. Presented by: Eric Carty-Fickes
Memory System Characterization of Commercial Workloads L.A. Barroso, K. Gharachorloo and E. Bugnion Western Research Laboratory Digital Equipment Corporation
Presented by: Eric Carty-Fickes

2. Introduction commercial workloads > engineering
but most still using scientific benchmarks (in 1998)
difficult to create commercial benchmarks
large, expensive, proprietary, changing
paper uses commercial workloads to study current trends

3. Database Workloads first two run on Oracle DB server OLTP
small r/w queries on part of DB
models banking req’s in dedicated mode
more kernel time; hides I/O
DSS (decision support systems)
long read-only queries on much of DB
models wholesaler’s SQL queries
fewer context-switches

4. Database Workloads Web Index Search doesn’t require DB server
multiple threads hide misses
read-only req’s and cached recent searches

5. Test Systems
4 processor AlphaServer 4100 and 8 processor 8400 for hardware testing
IPROBE tool for event counting
DCPI for profiling
ATOM for studying ORACLE
SimOS for testing architectural changes
models Alpha 21164
simplified, but still with some detail

6. Aspects of Testing 3 issues: memory size, I/O bandwidth, runtime
scale down DB
change block buffer cache sizes
OLTP and DSS: need to warm up SGA before testing; need to scale DB to be resident
Web Index: no scaling – same system

7. Hardware Results OLTP – higher CPI, maybe due to TPC-B
long secondary cache latency
lots of primary cache misses, esp Icache
dirty miss latency significant, lots of communication
DSS – lower CPI means this config works
only suggestion is larger 1st level caches
AltaVista – use 8400 just like original
good CPI, well written code
1st level caches important

8. Simulator Results
simulator like hardware, some cache and consistency differences = different timing
close cycle counts, miss rates
OLTP – test assoc and Bcache size
idle time increase when servers can’t hide I/O
lots of cache intricacies…
bigger caches = fewer replacemt, inst misses – more important for OLTP than DSS
bigger lines = more true sharing, less cold missing

9. Conclusions
scaled OLTP and DSS give a decent estimate of real performance
fairly narrow range of architectural issues explored
more processes/processor = less I/O latency, fewer dirty misses
simulators gloss over important details for ease of use (timing, OS, etc.)

10. Questions
Can you get enough information by scaling down the DB and playing tricks with block buffer sizes?