This paper presents NoSQ (short for no store queue), a microarchitecture that performs store-load communication without a store queue and without executing stores in the out-of-order engine. NoSQ implements store-load communication using speculative memory bypassing (SMB), the dynamic short-circuiting of DEF-store-load-USE chains to DEF-USE chains. Whereas previous proposals used SMB as an opportunistic complement to conventional store queue-based forwarding, NoSQ uses SMB as a store queue replacement. NoSQ relies on two supporting mechanisms. The first is an advanced store-load bypassing predictor that for a given dynamic load can predict whether that load will bypass and the identity of the communicating store. The second is an efficient verification mechanism for both bypassed and non-bpyassed loads using in-order load re-execution with an SMB-aware store vulnerability window (SVW) filter. The primary benefit of NoSQ is a simple, fast datapath that does not contain store-load forwarding hardware; all loads get their values either from the data cache or from the register file. Experiments show that this simpler design - despite being more speculative - slightly outperforms a conventional store-queue based design on most benchmarks (by 2% on average)

RENO is a modified MIPS R10000 register renamer that uses map-table "short-circuiting" to implement dynamic versions of several well-known static optimizations: move elimination, common subexpression elimination, register allocation, and constant folding. Because it implements these optimizations dynamically, RENO can apply optimizations in certain situations where static compilers cannot. Cycle-level simulation shows that RENO dynamically eliminates (i.e. optimizes away) 22% of the dynamic instructions in both SPECint2000 and MediaBench. RENO/sub CF/ is responsible for 12% and 17% of the eliminations, respectively. Because dataflow dependences are collapsed around eliminated instructions, performance improves by 8% and 13%, respectively. Alternatively, because eliminated instructions do not consume issue queue entries, physical registers, or issue, bypass, register file, and execution bandwidth, RENO can be used to absorb the performance impact of a significantly scaled-down execution core.

Conventional processors use a fully-associative store queue (SQ) to implement store-load forwarding. Associative search latency does not scale well to capacities and bandwidths required by wide-issue, large window processors. In this work, we improve SQ scalability by implementing store-load forwarding using speculative indexed access rather than associative search. Our design uses prediction to identify the single SQ entry from which each dynamic load is most likely to forward. When a load executes, it either obtains its value from the predicted SQ entry (if the address of the entry matches the load address) or the data cache (otherwise). A forwarding misprediction - detected by pre-commit filtered load reexecution - results in a pipeline flush. SQ index prediction is generally accurate, but for some loads it cannot reliably identify a single SQ entry. To avoid flushes on these difficult loads while keeping the single-SQ-access-per-load invariant, a second predictor delays difficult loads until all but the youngest of their "candidate" stores have committed. Our predictors are inspired by store-load dependence predictors for load scheduling (Store Sets and the Exclusive Collision Predictor) and unify load scheduling and forwarding. Experiments on the SPEC2000 and MediaBench benchmarks show that on an 8-way issue processor with a 512-entry reorder buffer, our technique performs within 3.3% of an ideal associative SQ (same latency as the data cache) and either matches or exceeds the performance of a realistic associative SQ (slower than data cache) on 31 of 47 programs.