The TRIPS system employs a new instruction set architecture (ISA) called Explicit Data Graph Execution (EDGE) that renegotiates the boundary between hardware and software to expose and exploit concurrency. EDGE ISAs use a block-atomic execution model in which blocks are composed of dataflow instructions. The goal of the TRIPS design is to mine concurrency for high performance while tolerating emerging technology scaling challenges, such as increasing wire delays and power consumption. This paper evaluates how well TRIPS meets this goal through a detailed ISA and performance analysis. We compare performance, using cycles counts, to commercial processors. On SPEC CPU2000, the Intel Core 2 outperforms compiled TRIPS code in most cases, although TRIPS matches a Pentium 4. On simple benchmarks, compiled TRIPS code outperforms the Core 2 by 10% and hand-optimized TRIPS code outperforms it by factor of 3. Compared to conventional ISAs, the block-atomic model provides a larger instruction window, increases concurrency at a cost of more instructions executed, and replaces register and memory accesses with more efficient direct instruction-to-instruction communication. Our analysis suggests ISA, microarchitecture, and compiler enhancements for addressing weaknesses in TRIPS and indicates that EDGE architectures have the potential to exploit greater concurrency in future technologies.

This paper analyzes the performance of the TRIPS prototype chip's block predictor. The prototype is the first implementation of the block-atomic TRIPS architecture, wherein the unit of execution is a TRIPS hyperblock. The TRIPS prototype predictor uses a two-step prediction process: it first predicts the exit from the current hyperblock and uses the predicted exit in conjunction with the current hyperblock's address to predict the next hyperblock. SPECint2000 and SPECfp2000 benchmarks record average misprediction rates of 11.5% and 4.3%, respectively, on the prototype chip. Simulation-driven analysis identifies short history lengths, inadequate offset bits in the branch target buffers, and aliasing in the exit and target predictors as the main reasons for the predictor inefficiency. If the above issues are addressed, block misprediction rates can be reduced by 15% for SPECint2000 and 22% for SPECfp2000. Using a perceptron-based analysis, we show that there is significant loss in correlation in our current hyperblocks. We conclude that while carefully tuned block predictors can achieve relatively lower misprediction rates, new predictor designs and correlation-aware hyperblock formation are necessary to bridge the gap between block prediction accuracies and branch prediction accuracies.

Modern chip multiprocessors (CMPs) are designed to exploit both instruction-level parallelism (ILP) within processors and thread-level parallelism (TLP) within and across processors. However, the number of processors and the granularity of each processor are fixed at design time. This paper evaluates a flexible architectural approach, called composable lightweight processors (or CLPs), that allows simple, low-power cores to be aggregated together dynamically, forming larger, more powerful single-threaded processors without changing the application binary. We evaluate one such design with 32 cores called TFlex, which can be configured as 32 dual-issue processors, or as a single 64-wide issue processor, or as any point in between. Use of an explicit data graph execution (EDGE) ISA enables the system to be fully composable, with no monolithic structures spanning the cores. Simulation results show that CLPs achieve an average performance boost of 42%, an average area-efficiency of 3.4x, and an average power-efficiency of 2x over a fixed architecture on a spectrum of single-threaded applications. Results also show that CLPs outperform a spectrum of fixed CMP architectures on a set of multitasking workloads.

Growing on-chip wire delays will cause many future microarchitectures to be distributed, in which hardware resources within a single processor become nodes on one or more switched micronetworks. Since large processor cores will require multiple clock cycles to traverse, control must be distributed, not centralized. This paper describes the control protocols in the TRIPS processor, a distributed, tiled microarchitecture that supports dynamic execution. It details each of the five types of reused tiles that compose the processor, the control and data networks that connect them, and the distributed microarchitectural protocols that implement instruction fetch, execution, flush, and commit. We also describe the physical design issues that arose when implementing the microarchitecture in a 170M transistor, 130nm ASIC prototype chip composed of two 16-wide issue distributed processor cores and a distributed 1MB non-uniform (NUCA) on-chip memory system

This paper describes the polymorphous TRIPS architecture that can be configured for different granularities and types of parallelism. The TRIPS architecture is the first in a class of post-RISC, dataflow-like instruction sets called explicit data-graph execution (EDGE). This EDGE ISA is coupled with hardware mechanisms that enable the processing cores and the on-chip memory system to be configured and combined in different modes for instruction, data, or thread-level parallelism. To adapt to small and large-grain concurrency, the TRIPS architecture prototype contains two out-of-order, 16-wide-issue grid processor cores, which can be partitioned when easily extractable fine-grained parallelism exists. This approach to polymorphism provides better performance across a wide range of application types than an approach in which many small processors are aggregated to run workloads with irregular parallelism. Our results show that high performance can be obtained in each of the three modes---ILP, TLP, and DLP---demonstrating the viability of the polymorphous coarse-grained approach for future microprocessors.