Microcode compaction with timing constraints

Abstract

At present, microcode compaction with timing constraints (abbreviated as MCTC) is still an open problem. Complex timing relation between microoperations greatly affects the optimization result of microcode. This paper begins with a survey of MCTC problems, then presents a formal description of MCTC and, on the basis of a systematic study of the characteristics of HCTC, presents a generally-oriented heuristic algorithm--CAS, which has a high success rate of scheduling and promises a good optimization result. Preliminary experiments indicate that CAS is better than other existing MCTC algorithms.

Instruction Scheduling with Release Times and Deadlines on ILP Processors

“…By using induction and the properties of forward scheduling and backward scheduling, we can prove the fol- v [5,12] v [6,15] v [6,15] v [8,15] 6 v [6, 15] v [8,10] v [8,10] v [4,8] v [5,13] v [2,6] v [3,7] Proof Suppose that there exists a feasible schedule σ ′ , but a schedule σ computed by our algorithm is not feasible. Let v k be the first late instruction and t the earliest integer time point satisfying 1) there are m k (σ(v k ) − t) instructions scheduled in the time interval [t, σ(v k )) on m k functional unit of type R(v k ) in σ, where m k is the number of functional units of type R(v k ), and 2) for each instruction …”

“…For example, in CNC systems [7], the output to motors must be sent at particular times to maintain high positioning accuracy of the machine tool. A number of researchers have studied the problem of scheduling timeconstrained instructions [1][2][3][4][5]. Palem and Simon [4] studied the problem of scheduling instructions with individual deadlines on an ILP processor with multiple identical functional units.…”

“…As a result, no feasible exists for the original problem instance P (v i ). v [3,14] v [3,12] v [3,15] v [5,15] v [5,15] v [5,12] v [6,15] v [6,15] v [5,14] v [8,15] v [3,10] 6 v [6, 15] v [8,10] v [8,10] v [4,9] v [2,6] Figure 2. The edge-consistent release times and deadlines in P Example 1 Consider a problem instance P with 14 instructions and an ILP processor with two heterogeneous functional units F 1 and F 2 .…”

“…Suppose that our algorithm has computed the 0-successortree consistent deadline of v 6 which is 7, we show how our algorithm computes the 4-successor-tree-consistent dead- [5,13] v [8,10] v [8,10] v [4,8] v [5,12] v [2,6] v [1,4] Lastly it applies disjoint union-find algorithm to find the successor-tree-consistent deadline which is 11. The l max (v i )-successor-tree-consistent deadline of each instruction v i is shown in Figure 6 where y in [x, y] beside each instruction v i is the l max (v i )-successor-tree-consistent deadline of v i .…”

Building a retargetable local instruction scheduler

“…A common heuristic used to determine priority 3,[23][24][25] is height in the graph. Height is defined as the longest path from a node to the sink, where path length is the sum of the min times.…”